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[FCSNEW.NET] ZeroToMastery - TensorFlow for Deep Learning Bootcamp Zero to Mastery

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[FCSNEW.NET] ZeroToMastery - TensorFlow for Deep Learning Bootcamp Zero to Mastery

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文件列表

  • 10. NLP Fundamentals in TensorFlow/16. Visualizing our model's learned word embeddings with TensorFlow's projector tool.mp4 282.2 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/23. Writing a preprocessing function to turn time series data into windows & labels.mp4 196.3 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/47. Model 7 Putting together the pieces of the puzzle of the N-BEATS model.mp4 181.0 MB
  • 11. Milestone Project 2 SkimLit/6. Writing a preprocessing function to structure our data for modelling.mp4 167.7 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/41. Model 7 Replicating the N-BEATS basic block with TensorFlow layer subclassing.mp4 159.7 MB
  • 10. NLP Fundamentals in TensorFlow/15. Model 1 Building, fitting and evaluating our first deep model on text data.mp4 158.4 MB
  • 10. NLP Fundamentals in TensorFlow/9. Setting up a TensorFlow TextVectorization layer to convert text to numbers.mp4 152.7 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/21. Preparing Model 3 (our first fine-tuned model).mp4 151.9 MB
  • 3. Neural network regression with TensorFlow/13. Evaluating a TensorFlow model part 3 (getting a model summary).mp4 149.0 MB
  • 11. Milestone Project 2 SkimLit/21. Model 4 Building a multi-input model (hybrid token + character embeddings).mp4 143.2 MB
  • 11. Milestone Project 2 SkimLit/17. Creating a character-level tokeniser with TensorFlow's TextVectorization layer.mp4 139.5 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/51. Model 8 Making and evaluating predictions with our ensemble model.mp4 136.3 MB
  • 10. NLP Fundamentals in TensorFlow/21. Discussing the intuition behind Conv1D neural networks for text and sequences.mp4 135.1 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/42. Model 7 Testing our N-BEATS block implementation with dummy data inputs.mp4 134.9 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/4. Downloading and turning our images into a TensorFlow BatchDataset.mp4 132.2 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/15. Breaking our CNN model down part 5 Looking inside a Conv2D layer.mp4 131.9 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/10. Getting a feature vector from our trained model.mp4 130.7 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/50. Model 8 Building, compiling and fitting an ensemble of models.mp4 127.4 MB
  • 10. NLP Fundamentals in TensorFlow/27. Fixing our data leakage issue with model 7 and retraining it.mp4 127.1 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/35. Model 5 Building, fitting and evaluating a LSTM (RNN) model on our Bitcoin data.mp4 126.9 MB
  • 4. Neural network classification in TensorFlow/19. Using callbacks to find a model's ideal learning rate.mp4 126.8 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/26. Model 1 Building, compiling and fitting a deep learning model on Bitcoin data.mp4 126.2 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/45. Model 7 Getting ready for residual connections.mp4 126.2 MB
  • 3. Neural network regression with TensorFlow/7. The major steps in modelling with TensorFlow.mp4 126.1 MB
  • 4. Neural network classification in TensorFlow/9. Creating a function to view our model's not so good predictions.mp4 125.8 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/9. Compiling and fitting our first Functional API model.mp4 124.4 MB
  • 11. Milestone Project 2 SkimLit/14. Model 1 Building, fitting and evaluating a Conv1D with token embeddings.mp4 123.8 MB
  • 10. NLP Fundamentals in TensorFlow/19. Model 3 Building, fitting and evaluating a GRU-cell powered RNN.mp4 123.5 MB
  • 3. Neural network regression with TensorFlow/27. Putting together what we've learned part 3 (improving our regression model).mp4 123.4 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/8. Downloading and inspecting our Bitcoin historical dataset.mp4 121.5 MB
  • 11. Milestone Project 2 SkimLit/29. Model 5 Completing the build of a tribrid embedding model for sequences.mp4 120.8 MB
  • 10. NLP Fundamentals in TensorFlow/18. Model 2 Building, fitting and evaluating our first TensorFlow RNN model (LSTM).mp4 120.0 MB
  • 10. NLP Fundamentals in TensorFlow/14. Creating a function to track and evaluate our model's results.mp4 119.7 MB
  • 10. NLP Fundamentals in TensorFlow/6. Becoming one with the data and visualizing a text dataset.mp4 119.6 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/14. Creating a confusion matrix for our model's 101 different classes.mp4 119.6 MB
  • 11. Milestone Project 2 SkimLit/4. Setting up our notebook for Milestone Project 2 (getting the data).mp4 119.0 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/18. Making predictions on our test images and evaluating them.mp4 118.6 MB
  • 11. Milestone Project 2 SkimLit/24. Model 4 Building, fitting and evaluating a hybrid embedding model.mp4 117.9 MB
  • 10. NLP Fundamentals in TensorFlow/20. Model 4 Building, fitting and evaluating a bidirectional RNN model.mp4 114.1 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/16. Building Model 1 (with a data augmentation layer and 1% of training data).mp4 110.4 MB
  • 4. Neural network classification in TensorFlow/17. Getting great results in less time by tweaking the learning rate.mp4 109.6 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/17. Building Model 2 (with a data augmentation layer and 10% of training data).mp4 109.5 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/20. Breaking our CNN model down part 10 Visualizing our augmented data.mp4 108.9 MB
  • 11. Milestone Project 2 SkimLit/35. Congratulations and your challenge before heading to the next module.mp4 108.5 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/8. Creating our first model with the TensorFlow Keras Functional API.mp4 108.3 MB
  • 10. NLP Fundamentals in TensorFlow/11. Creating an Embedding layer to turn tokenised text into embedding vectors.mp4 108.3 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/27. Multi-class CNN's part 1 Becoming one with the data.mp4 108.3 MB
  • 4. Neural network classification in TensorFlow/16. Non-linearity part 5 Replicating non-linear activation functions from scratch.mp4 106.1 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/28. Model 2 Building, fitting and evaluating a deep model with a larger window size-27.mp4 105.6 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/34. Model 4 Building, fitting and evaluating a Conv1D model on our Bitcoin data.mp4 104.8 MB
  • 11. Milestone Project 2 SkimLit/5. Visualizing examples from the dataset (becoming one with the data).mp4 104.4 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/7. Building an end to end CNN Model.mp4 102.5 MB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/10. Comparing Our Model's Results.mp4 101.7 MB
  • 11. Milestone Project 2 SkimLit/1. Introduction to Milestone Project 2 SkimLit.mp4 100.9 MB
  • 4. Neural network classification in TensorFlow/27. Multi-class classification part 3 Building a multi-class classification model.mp4 100.4 MB
  • 9. Milestone Project 1 Food Vision Big™/7. Batching and preparing our datasets (to make them run fast).mp4 99.8 MB
  • 11. Milestone Project 2 SkimLit/11. Creating a text vectoriser to map our tokens (text) to numbers.mp4 99.5 MB
  • 3. Neural network regression with TensorFlow/25. Putting together what we've learned part 1 (preparing a dataset).mp4 99.4 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/29. Model 3 Building, fitting and evaluating a model with a larger horizon size.mp4 99.2 MB
  • 11. Milestone Project 2 SkimLit/15. Preparing a pretrained embedding layer from TensorFlow Hub for Model 2.mp4 98.9 MB
  • 4. Neural network classification in TensorFlow/14. Non-linearity part 3 Upgrading our non-linear model with more layers.mp4 98.8 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/8. Using a GPU to run our CNN model 5x faster.mp4 98.0 MB
  • 4. Neural network classification in TensorFlow/11. Make our poor classification model work for a regression dataset.mp4 97.8 MB
  • 10. NLP Fundamentals in TensorFlow/31. Downloading a pretrained model and preparing data to investigate predictions.mp4 97.5 MB
  • 11. Milestone Project 2 SkimLit/19. Model 3 Building, fitting and evaluating a Conv1D model on character embeddings.mp4 97.3 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/32. Multi-class CNN's part 6 Trying to fix overfitting by removing layers.mp4 96.9 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/15. Evaluating every individual class in our dataset.mp4 96.7 MB
  • 3. Neural network regression with TensorFlow/10. Steps in improving a model with TensorFlow part 3.mp4 96.6 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/11. Making predictions with our trained model on 25,250 test samples.mp4 95.9 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/2. Getting helper functions ready and downloading data to model.mp4 95.1 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/18. Breaking our CNN model down part 8 Reducing overfitting with Max Pooling.mp4 94.9 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/43. Model 7 Creating a performant data pipeline for the N-BEATS model with tf.data.mp4 94.9 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/27. Creating a function to make predictions with our trained models.mp4 94.6 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/35. Multi-class CNN's part 9 Making predictions with our model on custom images.mp4 94.4 MB
  • 10. NLP Fundamentals in TensorFlow/23. Using TensorFlow Hub for pretrained word embeddings (transfer learning for NLP).mp4 94.2 MB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/2. Downloading and preparing data for our first transfer learning model.mp4 93.7 MB
  • 4. Neural network classification in TensorFlow/34. What patterns is our model learning.mp4 93.0 MB
  • 11. Milestone Project 2 SkimLit/32. Bringing SkimLit to life!!! (fitting and evaluating Model 5).mp4 92.7 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/59. Model 9 Creating a function to make forecasts into the future.mp4 91.8 MB
  • 4. Neural network classification in TensorFlow/7. Building a not very good classification model with TensorFlow.mp4 91.8 MB
  • 9. Milestone Project 1 Food Vision Big™/6. Creating a preprocessing function to prepare our data for modelling.mp4 91.1 MB
  • 10. NLP Fundamentals in TensorFlow/4. The typical architecture of a Recurrent Neural Network (RNN).mp4 91.0 MB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/5. Building and compiling a TensorFlow Hub feature extraction model.mp4 90.9 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/33. Multi-class CNN's part 7 Trying to fix overfitting with data augmentation.mp4 90.5 MB
  • 3. Neural network regression with TensorFlow/19. Setting up TensorFlow modelling experiments part 1 (start with a simple model).mp4 90.3 MB
  • 11. Milestone Project 2 SkimLit/30. Visually inspecting the architecture of our tribrid embedding model.mp4 90.2 MB
  • 10. NLP Fundamentals in TensorFlow/34. Understanding the concept of the speedscore tradeoff.mp4 90.1 MB
  • 10. NLP Fundamentals in TensorFlow/2. Introduction to Natural Language Processing (NLP) and Sequence Problems.mp4 89.0 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/21. Plotting and visualizing the samples our model got most wrong.mp4 88.8 MB
  • 9. Milestone Project 1 Food Vision Big™/11. Turning on mixed precision training with TensorFlow.mp4 88.3 MB
  • 4. Neural network classification in TensorFlow/31. Multi-class classification part 7 Evaluating our model.mp4 88.0 MB
  • 11. Milestone Project 2 SkimLit/8. Turning our target labels into numbers (ML models require numbers).mp4 87.7 MB
  • 4. Neural network classification in TensorFlow/28. Multi-class classification part 4 Improving performance with normalisation.mp4 87.3 MB
  • 9. Milestone Project 1 Food Vision Big™/4. Introduction to TensorFlow Datasets (TFDS).mp4 86.2 MB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/9. Different Types of Transfer Learning.mp4 86.2 MB
  • 3. Neural network regression with TensorFlow/26. Putting together what we've learned part 2 (building a regression model).mp4 85.6 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/13. Building a data augmentation layer to use inside our model.mp4 85.4 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/38. Preparing our multivariate time series for a model.mp4 84.7 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/46. Model 7 Outlining the steps we're going to take to build the N-BEATS model.mp4 83.6 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/36. Investigating how to turn our univariate time series into multivariate.mp4 83.1 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/54. Plotting the prediction intervals of our ensemble model predictions.mp4 83.1 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/10. Improving our non-CNN model by adding more layers.mp4 82.8 MB
  • 2. Deep Learning and TensorFlow Fundamentals/29. Making sure our tensor operations run really fast on GPUs.mp4 82.0 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/40. Model 7 Discussing what we're going to be doing with the N-BEATS algorithm.mp4 81.9 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/16. Model 0 Making and visualizing a naive forecast model.mp4 81.7 MB
  • 9. Milestone Project 1 Food Vision Big™/15. Introducing your Milestone Project 1 challenge build a model to beat DeepFood.mp4 81.0 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/55. (Optional) Discussing the types of uncertainty in machine learning.mp4 81.0 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/13. Breaking our CNN model down part 3 Loading our data with ImageDataGenerator.mp4 80.8 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/20. Writing code to uncover our model's most wrong predictions.mp4 80.8 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/25. Writing a helper function to load and preprocessing custom images.mp4 80.6 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/22. Breaking our CNN model down part 12 Discovering the power of shuffling data.mp4 80.5 MB
  • 4. Neural network classification in TensorFlow/24. Making our confusion matrix prettier.mp4 80.1 MB
  • 11. Milestone Project 2 SkimLit/31. Creating multi-level data input pipelines for Model 5 with the tf.data API.mp4 80.0 MB
  • 11. Milestone Project 2 SkimLit/26. Encoding the line number feature to used with Model 5.mp4 79.1 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/11. Reading in our Bitcoin data with Python's CSV module.mp4 79.0 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/62. Model 10 Building a model to predict on turkey data (why forecasting is BS).mp4 78.6 MB
  • 11. Milestone Project 2 SkimLit/16. Model 2 Building, fitting and evaluating a Conv1D model with token embeddings.mp4 78.4 MB
  • 9. Milestone Project 1 Food Vision Big™/13. Checking to see if our model is using mixed precision training layer by layer.mp4 78.1 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/52. Discussing the importance of prediction intervals in forecasting.mp4 77.6 MB
  • 2. Deep Learning and TensorFlow Fundamentals/10. Creating your first tensors with TensorFlow and tf.constant().mp4 77.5 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/33. Preparing data for building a Conv1D model.mp4 77.5 MB
  • 9. Milestone Project 1 Food Vision Big™/5. Exploring and becoming one with the data (Food101 from TensorFlow Datasets).mp4 77.1 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/12. Breaking our CNN model down part 2 Preparing to load our data.mp4 76.9 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/44. Model 7 Setting up hyperparameters for the N-BEATS algorithm.mp4 76.9 MB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/8. Building and training a pre-trained EfficientNet model on our data.mp4 76.8 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/18. Implementing MASE with TensorFlow.mp4 76.6 MB
  • 10. NLP Fundamentals in TensorFlow/30. Saving and loading in a trained NLP model with TensorFlow.mp4 76.6 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/63. Comparing the results of all of our models and discussing where to go next.mp4 76.5 MB
  • 4. Neural network classification in TensorFlow/4. Typical architecture of neural network classification models with TensorFlow.mp4 76.4 MB
  • 10. NLP Fundamentals in TensorFlow/10. Mapping the TextVectorization layer to text data and turning it into numbers.mp4 76.3 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/60. Model 9 Plotting our model's future forecasts.mp4 76.1 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/9. Trying a non-CNN model on our image data.mp4 75.3 MB
  • 10. NLP Fundamentals in TensorFlow/28. Comparing all our modelling experiments evaluation metrics.mp4 75.1 MB
  • 9. Milestone Project 1 Food Vision Big™/12. Creating a feature extraction model capable of using mixed precision training.mp4 75.1 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/30. Adjusting the evaluation function to work for predictions with larger horizons.mp4 75.0 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/15. Visualizing what happens when images pass through our data augmentation layer.mp4 74.9 MB
  • 11. Milestone Project 2 SkimLit/12. Creating a custom token embedding layer with TensorFlow.mp4 74.5 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/32. Comparing our modelling experiments so far and discussing autocorrelation.mp4 74.4 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/21. Formatting data Part 2 Creating a function to label our windowed time series.mp4 74.1 MB
  • 10. NLP Fundamentals in TensorFlow/26. Model 7 Building, training and evaluating a transfer learning model on 10% data.mp4 73.8 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/22. Making predictions on and plotting our own custom images.mp4 73.5 MB
  • 3. Neural network regression with TensorFlow/22. How to save a TensorFlow model.mp4 73.5 MB
  • 10. NLP Fundamentals in TensorFlow/17. High-level overview of Recurrent Neural Networks (RNNs) + where to learn more.mp4 73.4 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/17. Creating a function to load and prepare images for making predictions.mp4 73.4 MB
  • 3. Neural network regression with TensorFlow/23. How to load and use a saved TensorFlow model.mp4 73.3 MB
  • 3. Neural network regression with TensorFlow/21. Comparing and tracking your TensorFlow modelling experiments.mp4 72.6 MB
  • 10. NLP Fundamentals in TensorFlow/29. Uploading our model's training logs to TensorBoard and comparing them.mp4 72.3 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/2. Importing a script full of helper functions (and saving lots of space).mp4 72.2 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/37. Creating and plotting a multivariate time series with BTC price and block reward.mp4 72.1 MB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/6. Blowing our previous models out of the water with transfer learning.mp4 71.9 MB
  • 16. Appendix Pandas for Data Analysis/9. Selecting and Viewing Data with Pandas Part 2.mp4 71.3 MB
  • 3. Neural network regression with TensorFlow/20. Setting up TensorFlow modelling experiments part 2 (increasing complexity).mp4 71.2 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/10. Downloading a pretrained model to make and evaluate predictions with.mp4 71.2 MB
  • 10. NLP Fundamentals in TensorFlow/8. Converting text data to numbers using tokenisation and embeddings (overview).mp4 71.0 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/25. Preparing our final modelling experiment (Model 4).mp4 70.3 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/21. Breaking our CNN model down part 11 Training a CNN model on augmented data.mp4 70.2 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/26. Making a prediction on a custom image with our trained CNN.mp4 70.0 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/17. Breaking our CNN model down part 7 Evaluating our CNN's training curves.mp4 69.7 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/17. Discussing some of the most common time series evaluation metrics.mp4 69.7 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/7. Unfreezing some layers in our base model to prepare for fine-tuning.mp4 69.7 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/12. Downloading and preparing the data for Model 1 (1 percent of training data).mp4 69.6 MB
  • 3. Neural network regression with TensorFlow/29. Preprocessing data with feature scaling part 2 (normalising our data).mp4 69.5 MB
  • 10. NLP Fundamentals in TensorFlow/24. Model 6 Building, training and evaluating a transfer learning model for NLP.mp4 69.0 MB
  • 4. Neural network classification in TensorFlow/5. Creating and viewing classification data to model.mp4 68.8 MB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/3. Introducing Callbacks in TensorFlow and making a callback to track our models.mp4 68.8 MB
  • 2. Deep Learning and TensorFlow Fundamentals/18. Matrix multiplication with tensors part 1.mp4 68.6 MB
  • 2. Deep Learning and TensorFlow Fundamentals/19. Matrix multiplication with tensors part 2.mp4 68.5 MB
  • 2. Deep Learning and TensorFlow Fundamentals/14. Creating tensors from NumPy arrays.mp4 68.4 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/19. Creating a function to evaluate our model's forecasts with various metrics.mp4 68.2 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/26. Fine-tuning Model 4 on 100% of the training data and evaluating its results.mp4 68.1 MB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/4. Exploring the TensorFlow Hub website for pretrained models.mp4 68.0 MB
  • 16. Appendix Pandas for Data Analysis/10. Manipulating Data.mp4 67.6 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/24. Turning our windowed time series data into training and test sets.mp4 67.5 MB
  • 11. Milestone Project 2 SkimLit/22. Model 4 Plotting and visually exploring different data inputs.mp4 67.4 MB
  • 10. NLP Fundamentals in TensorFlow/13. Model 0 Building a baseline model to try and improve upon.mp4 67.4 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/29. Multi-class CNN's part 3 Building a multi-class CNN model.mp4 67.2 MB
  • 4. Neural network classification in TensorFlow/20. Training and evaluating a model with an ideal learning rate.mp4 66.9 MB
  • 2. Deep Learning and TensorFlow Fundamentals/24. Finding the positional minimum and maximum of a tensor (argmin and argmax).mp4 66.9 MB
  • 4. Neural network classification in TensorFlow/15. Non-linearity part 4 Modelling our non-linear data once and for all.mp4 66.7 MB
  • 3. Neural network regression with TensorFlow/9. Steps in improving a model with TensorFlow part 2.mp4 66.7 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/27. Comparing our modelling experiment results in TensorBoard.mp4 66.5 MB
  • 10. NLP Fundamentals in TensorFlow/12. Discussing the various modelling experiments we're going to run.mp4 66.3 MB
  • 4. Neural network classification in TensorFlow/8. Trying to improve our not very good classification model.mp4 65.7 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/5. Becoming One With Data Part 2.mp4 65.7 MB
  • 3. Neural network regression with TensorFlow/28. Preprocessing data with feature scaling part 1 (what is feature scaling).mp4 65.6 MB
  • 10. NLP Fundamentals in TensorFlow/25. Preparing subsets of data for model 7 (same as model 6 but 10% of data).mp4 64.7 MB
  • 9. Milestone Project 1 Food Vision Big™/2. Making sure we have access to the right GPU for mixed precision training.mp4 64.4 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/11. Breaking our CNN model down part 1 Becoming one with the data.mp4 64.3 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/61. Model 10 Introducing the turkey problem and making data for it.mp4 64.3 MB
  • 4. Neural network classification in TensorFlow/12. Non-linearity part 1 Straight lines and non-straight lines.mp4 64.1 MB
  • 11. Milestone Project 2 SkimLit/7. Performing visual data analysis on our preprocessed text.mp4 64.1 MB
  • 4. Neural network classification in TensorFlow/25. Putting things together with multi-class classification part 1 Getting the data.mp4 63.4 MB
  • 3. Neural network regression with TensorFlow/4. Creating sample regression data (so we can model it).mp4 63.3 MB
  • 9. Milestone Project 1 Food Vision Big™/14. Training and evaluating a feature extraction model (Food Vision Big™).mp4 63.0 MB
  • 11. Milestone Project 2 SkimLit/10. Preparing our data for deep sequence models.mp4 62.8 MB
  • 2. Deep Learning and TensorFlow Fundamentals/22. Tensor aggregation (finding the min, max, mean & more).mp4 62.5 MB
  • 16. Appendix Pandas for Data Analysis/11. Manipulating Data 2.mp4 62.5 MB
  • 16. Appendix Pandas for Data Analysis/12. Manipulating Data 3.mp4 62.5 MB
  • 11. Milestone Project 2 SkimLit/13. Creating fast loading dataset with the TensorFlow tf.data API.mp4 62.2 MB
  • 17. Appendix NumPy/14. Exercise Nut Butter Store Sales.mp4 61.9 MB
  • 11. Milestone Project 2 SkimLit/34. Saving, loading & testing our best performing model.mp4 61.8 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/31. Model 3 Visualizing the results.mp4 61.7 MB
  • 2. Deep Learning and TensorFlow Fundamentals/12. Creating random tensors with TensorFlow.mp4 61.6 MB
  • 11. Milestone Project 2 SkimLit/9. Model 0 Creating, fitting and evaluating a baseline model for SkimLit.mp4 61.3 MB
  • 2. Deep Learning and TensorFlow Fundamentals/13. Shuffling the order of tensors.mp4 60.7 MB
  • 16. Appendix Pandas for Data Analysis/5. Series, Data Frames and CSVs.mp4 60.7 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/15. Discussing the various modelling experiments were going to be running.mp4 60.6 MB
  • 3. Neural network regression with TensorFlow/30. Preprocessing data with feature scaling part 3 (fitting a model on scaled data).mp4 60.4 MB
  • 3. Neural network regression with TensorFlow/15. Evaluating a TensorFlow model part 5 (visualising a model's predictions).mp4 59.5 MB
  • 11. Milestone Project 2 SkimLit/18. Creating a character-level embedding layer with tf.keras.layers.Embedding.mp4 59.2 MB
  • 2. Deep Learning and TensorFlow Fundamentals/16. Indexing and expanding tensors.mp4 59.2 MB
  • 11. Milestone Project 2 SkimLit/28. Model 5 Building the foundations of a tribrid embedding model.mp4 59.1 MB
  • 10. NLP Fundamentals in TensorFlow/5. Preparing a notebook for our first NLP with TensorFlow project.mp4 58.7 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/16. Plotting our model's F1-scores for each separate class.mp4 58.7 MB
  • 17. Appendix NumPy/17. Turn Images Into NumPy Arrays.mp4 58.5 MB
  • 11. Milestone Project 2 SkimLit/2. What we're going to cover in Milestone Project 2 (NLP for medical abstracts).mp4 58.4 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/5. What can be forecast.mp4 58.1 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/56. Model 9 Preparing data to create a model capable of predicting into the future.mp4 57.6 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/14. Breaking our CNN model down part 4 Building a baseline CNN model.mp4 57.6 MB
  • 10. NLP Fundamentals in TensorFlow/32. Visualizing our model's most wrong predictions.mp4 57.3 MB
  • 2. Deep Learning and TensorFlow Fundamentals/15. Getting information from your tensors (tensor attributes).mp4 57.3 MB
  • 10. NLP Fundamentals in TensorFlow/33. Making and visualizing predictions on the test dataset.mp4 57.1 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/39. Model 6 Building, fitting and evaluating a multivariate time series model.mp4 57.1 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/23. Comparing our model's results before and after fine-tuning.mp4 56.8 MB
  • 3. Neural network regression with TensorFlow/12. Evaluating a TensorFlow model part 2 (the three datasets).mp4 56.7 MB
  • 4. Neural network classification in TensorFlow/1. Introduction to neural network classification in TensorFlow.mp4 56.6 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/36. Saving and loading our trained CNN model.mp4 56.4 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/53. Getting the upper and lower bounds of our prediction intervals.mp4 56.1 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/5. Creating a headless EfficientNetB0 model with data augmentation built in.mp4 55.3 MB
  • 3. Neural network regression with TensorFlow/14. Evaluating a TensorFlow model part 4 (visualising a model's layers).mp4 55.1 MB
  • 11. Milestone Project 2 SkimLit/23. Crafting multi-input fast loading tf.data datasets for Model 4.mp4 54.9 MB
  • 17. Appendix NumPy/9. Manipulating Arrays.mp4 54.5 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/16. Breaking our CNN model down part 6 Compiling and fitting our baseline CNN.mp4 54.1 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/3. What is a time series problem and example forecasting problems at Uber.mp4 53.5 MB
  • 17. Appendix NumPy/13. Dot Product vs Element Wise.mp4 53.5 MB
  • 10. NLP Fundamentals in TensorFlow/22. Model 5 Building, fitting and evaluating a 1D CNN for text.mp4 53.4 MB
  • 2. Deep Learning and TensorFlow Fundamentals/20. Matrix multiplication with tensors part 3.mp4 52.9 MB
  • 11. Milestone Project 2 SkimLit/33. Comparing the performance of all of our modelling experiments.mp4 52.7 MB
  • 3. Neural network regression with TensorFlow/24. (Optional) How to save and download files from Google Colab.mp4 52.6 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/3. Downloading an image dataset for our first Food Vision model.mp4 52.5 MB
  • 16. Appendix Pandas for Data Analysis/7. Describing Data with Pandas.mp4 52.3 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/19. Fitting and evaluating Model 2 (and saving its weights using ModelCheckpoint).mp4 51.8 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/28. Multi-class CNN's part 2 Preparing our data (turning it into tensors).mp4 51.7 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/2. Introduction to Convolutional Neural Networks (CNNs) with TensorFlow.mp4 51.6 MB
  • 4. Neural network classification in TensorFlow/30. Multi-class classification part 6 Finding the ideal learning rate.mp4 51.4 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/1. Introduction to Computer Vision with TensorFlow.mp4 50.7 MB
  • 2. Deep Learning and TensorFlow Fundamentals/4. What is deep learning already being used for.mp4 50.1 MB
  • 17. Appendix NumPy/5. NumPy DataTypes and Attributes.mp4 49.8 MB
  • 2. Deep Learning and TensorFlow Fundamentals/11. Creating tensors with TensorFlow and tf.Variable().mp4 49.3 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/18. Creating a ModelCheckpoint to save our model's weights during training.mp4 49.1 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/48. Model 7 Plotting the N-BEATS algorithm we've created and admiring its beauty.mp4 48.5 MB
  • 2. Deep Learning and TensorFlow Fundamentals/21. Changing the datatype of tensors.mp4 48.4 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/22. Fitting and evaluating Model 3 (our first fine-tuned model).mp4 48.1 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/6. Fitting and evaluating our biggest transfer learning model yet.mp4 47.9 MB
  • 17. Appendix NumPy/8. Viewing Arrays and Matrices.mp4 47.8 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/20. Discussing other non-TensorFlow kinds of time series forecasting models.mp4 47.6 MB
  • 2. Deep Learning and TensorFlow Fundamentals/23. Tensor troubleshooting example (updating tensor datatypes).mp4 47.4 MB
  • 3. Neural network regression with TensorFlow/11. Evaluating a TensorFlow model part 1 (visualise, visualise, visualise).mp4 47.1 MB
  • 11. Milestone Project 2 SkimLit/27. Encoding the total lines feature to be used with Model 5.mp4 47.0 MB
  • 11. Milestone Project 2 SkimLit/3. SkimLit inputs and outputs.mp4 46.9 MB
  • 3. Neural network regression with TensorFlow/16. Evaluating a TensorFlow model part 6 (common regression evaluation metrics).mp4 46.5 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/8. Fine-tuning our feature extraction model and evaluating its performance.mp4 46.3 MB
  • 4. Neural network classification in TensorFlow/18. Using the TensorFlow History object to plot a model's loss curves.mp4 46.2 MB
  • 16. Appendix Pandas for Data Analysis/8. Selecting and Viewing Data with Pandas.mp4 45.9 MB
  • 2. Deep Learning and TensorFlow Fundamentals/5. What is and why use TensorFlow.mp4 45.9 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/9. Different kinds of time series patterns & different amounts of feature variables.mp4 45.7 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/19. Breaking our CNN model down part 9 Reducing overfitting with data augmentation.mp4 45.6 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/9. Saving and loading our trained model.mp4 45.5 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/25. Creating a modelling checkpoint callback to save our best performing model.mp4 45.2 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/1. Introduction to Transfer Learning in TensorFlow Part 2 Fine-tuning.mp4 45.1 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/22. Discussing the use of windows and horizons in time series data.mp4 44.7 MB
  • 17. Appendix NumPy/10. Manipulating Arrays 2.mp4 44.6 MB
  • 11. Milestone Project 2 SkimLit/20. Discussing how we're going to build Model 4 (character + token embeddings).mp4 44.6 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/58. Model 9 Discussing what's required for our model to make future predictions.mp4 44.2 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/30. Multi-class CNN's part 4 Fitting a multi-class CNN model to the data.mp4 43.9 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/14. Creating a plotting function to visualize our time series data.mp4 43.8 MB
  • 1. Introduction/1. TensorFlow for Deep Learning Zero to Mastery.mp4 43.5 MB
  • 11. Milestone Project 2 SkimLit/25. Model 5 Adding positional embeddings via feature engineering (overview).mp4 43.3 MB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/7. Plotting the loss curves of our ResNet feature extraction model.mp4 43.3 MB
  • 9. Milestone Project 1 Food Vision Big™/8. Exploring what happens when we batch and prefetch our data.mp4 43.1 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/11. Drilling into the concept of a feature vector (a learned representation).mp4 42.6 MB
  • 2. Deep Learning and TensorFlow Fundamentals/27. Trying out more tensor math operations.mp4 42.5 MB
  • 2. Deep Learning and TensorFlow Fundamentals/26. One-hot encoding tensors.mp4 42.5 MB
  • 4. Neural network classification in TensorFlow/33. Multi-class classification part 9 Visualising random model predictions.mp4 42.3 MB
  • 10. NLP Fundamentals in TensorFlow/7. Splitting data into training and validation sets.mp4 42.3 MB
  • 9. Milestone Project 1 Food Vision Big™/9. Creating modelling callbacks for our feature extraction model.mp4 42.3 MB
  • 4. Neural network classification in TensorFlow/23. Creating our first confusion matrix (to see where our model is getting confused).mp4 41.8 MB
  • 17. Appendix NumPy/6. Creating NumPy Arrays.mp4 41.6 MB
  • 2. Deep Learning and TensorFlow Fundamentals/2. Why use deep learning.mp4 41.4 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/12. Creating train and test splits for time series (the wrong way).mp4 40.9 MB
  • 16. Appendix Pandas for Data Analysis/14. How To Download The Course Assignments.mp4 40.7 MB
  • 3. Neural network regression with TensorFlow/2. Inputs and outputs of a neural network regression model.mp4 40.5 MB
  • 3. Neural network regression with TensorFlow/17. Evaluating a TensorFlow regression model part 7 (mean absolute error).mp4 40.4 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/20. Loading and comparing saved weights to our existing trained Model 2.mp4 40.1 MB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/1. What is and why use transfer learning.mp4 38.9 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/24. Downloading and preparing data for our biggest experiment yet (Model 4).mp4 38.4 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/24. Downloading a custom image to make predictions on.mp4 38.4 MB
  • 10. NLP Fundamentals in TensorFlow/3. Example NLP inputs and outputs.mp4 38.2 MB
  • 4. Neural network classification in TensorFlow/13. Non-linearity part 2 Building our first neural network with non-linearity.mp4 38.0 MB
  • 3. Neural network regression with TensorFlow/1. Introduction to Neural Network Regression with TensorFlow.mp4 37.3 MB
  • 2. Deep Learning and TensorFlow Fundamentals/3. What are neural networks.mp4 36.9 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/57. Model 9 Building, compiling and fitting a future predictions model.mp4 36.7 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/7. Time series forecasting inputs and outputs.mp4 36.4 MB
  • 3. Neural network regression with TensorFlow/3. Anatomy and architecture of a neural network regression model.mp4 36.0 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/23. Breaking our CNN model down part 13 Exploring options to improve our model.mp4 35.9 MB
  • 15. Appendix Machine Learning and Data Science Framework/5. Types of Machine Learning Problems.mp4 35.6 MB
  • 17. Appendix NumPy/12. Reshape and Transpose.mp4 35.4 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/19. Discussing the benefits of finding your model's most wrong predictions.mp4 35.4 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/13. Confirming our model's predictions are in the same order as the test labels.mp4 34.3 MB
  • 17. Appendix NumPy/7. NumPy Random Seed.mp4 34.0 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/4. Becoming One With Data.mp4 32.7 MB
  • 4. Neural network classification in TensorFlow/2. Example classification problems (and their inputs and outputs).mp4 32.3 MB
  • 2. Deep Learning and TensorFlow Fundamentals/28. Exploring TensorFlow and NumPy's compatibility.mp4 32.3 MB
  • 17. Appendix NumPy/11. Standard Deviation and Variance.mp4 32.2 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/34. Multi-class CNN's part 8 Things you could do to improve your CNN model.mp4 31.8 MB
  • 4. Neural network classification in TensorFlow/3. Input and output tensors of classification problems.mp4 31.2 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/13. Creating train and test splits for time series (the right way).mp4 31.0 MB
  • 3. Neural network regression with TensorFlow/8. Steps in improving a model with TensorFlow part 1.mp4 30.7 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/12. Unravelling our test dataset for comparing ground truth labels to predictions.mp4 29.8 MB
  • 4. Neural network classification in TensorFlow/26. Multi-class classification part 2 Becoming one with the data.mp4 29.8 MB
  • 2. Deep Learning and TensorFlow Fundamentals/17. Manipulating tensors with basic operations.mp4 29.5 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/10. Visualizing our Bitcoin historical data with pandas.mp4 29.5 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/49. Model 8 Ensemble model overview.mp4 29.2 MB
  • 4. Neural network classification in TensorFlow/21. Introducing more classification evaluation methods.mp4 28.9 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/2. Introduction to Milestone Project 3 (BitPredict) & where you can get help.mp4 28.8 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/31. Multi-class CNN's part 5 Evaluating our multi-class CNN model.mp4 28.0 MB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/6. Becoming One With Data Part 3.mp4 27.7 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/4. Creating a data augmentation layer to use with our model.mp4 27.7 MB
  • 9. Milestone Project 1 Food Vision Big™/1. Introduction to Milestone Project 1 Food Vision Big™.mp4 27.1 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/3. Outlining the model we're going to build and building a ModelCheckpoint callback.mp4 27.1 MB
  • 15. Appendix Machine Learning and Data Science Framework/12. Modelling - Comparison.mp4 27.1 MB
  • 14. Appendix Machine Learning Primer/5. How Did We Get Here.mp4 26.8 MB
  • 4. Neural network classification in TensorFlow/32. Multi-class classification part 8 Creating a confusion matrix.mp4 25.7 MB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/1. Introduction to Transfer Learning Part 3 Scaling Up.mp4 24.5 MB
  • 14. Appendix Machine Learning Primer/4. Exercise Machine Learning Playground.mp4 24.1 MB
  • 4. Neural network classification in TensorFlow/6. Checking the input and output shapes of our classification data.mp4 23.8 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/6. What we're going to cover (broadly).mp4 23.7 MB
  • 9. Milestone Project 1 Food Vision Big™/3. Getting helper functions ready.mp4 23.6 MB
  • 4. Neural network classification in TensorFlow/22. Finding the accuracy of our classification model.mp4 23.0 MB
  • 14. Appendix Machine Learning Primer/2. What is Machine Learning.mp4 21.5 MB
  • 3. Neural network regression with TensorFlow/18. Evaluating a TensorFlow regression model part 7 (mean square error).mp4 21.4 MB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/4. Example forecasting problems in daily life.mp4 21.3 MB
  • 2. Deep Learning and TensorFlow Fundamentals/25. Squeezing a tensor (removing all 1-dimension axes).mp4 21.2 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/3. Exercise Imposter Syndrome.mp4 20.7 MB
  • 17. Appendix NumPy/16. Sorting Arrays.mp4 20.3 MB
  • 15. Appendix Machine Learning and Data Science Framework/8. Features In Data.mp4 20.1 MB
  • 17. Appendix NumPy/15. Comparison Operators.mp4 20.0 MB
  • 1. Introduction/2. Course Outline.mp4 19.4 MB
  • 2. Deep Learning and TensorFlow Fundamentals/1. What is deep learning.mp4 19.3 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/6. Comparing the TensorFlow Keras Sequential API versus the Functional API.mp4 18.5 MB
  • 2. Deep Learning and TensorFlow Fundamentals/6. What is a Tensor.mp4 17.6 MB
  • 2. Deep Learning and TensorFlow Fundamentals/7. What we're going to cover throughout the course.mp4 17.4 MB
  • 15. Appendix Machine Learning and Data Science Framework/6. Types of Data.mp4 16.7 MB
  • 4. Neural network classification in TensorFlow/29. Multi-class classification part 5 Comparing normalised and non-normalised data.mp4 16.1 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/28. How to view and delete previous TensorBoard experiments.mp4 16.0 MB
  • 14. Appendix Machine Learning Primer/3. AIMachine LearningData Science.mp4 15.9 MB
  • 15. Appendix Machine Learning and Data Science Framework/9. Modelling - Splitting Data.mp4 15.8 MB
  • 15. Appendix Machine Learning and Data Science Framework/15. Tools We Will Use.mp4 15.3 MB
  • 16. Appendix Pandas for Data Analysis/4. Pandas Introduction.mp4 15.3 MB
  • 14. Appendix Machine Learning Primer/9. What Is Machine Learning Round 2.mp4 14.7 MB
  • 2. Deep Learning and TensorFlow Fundamentals/8. How to approach this course.mp4 14.5 MB
  • 15. Appendix Machine Learning and Data Science Framework/10. Modelling - Picking the Model.mp4 13.5 MB
  • 15. Appendix Machine Learning and Data Science Framework/4. 6 Step Machine Learning Framework.mp4 13.4 MB
  • 14. Appendix Machine Learning Primer/7. Types of Machine Learning.mp4 13.3 MB
  • 15. Appendix Machine Learning and Data Science Framework/14. Experimentation.mp4 12.4 MB
  • 17. Appendix NumPy/3. NumPy Introduction.mp4 12.3 MB
  • 17. Appendix NumPy/2. Section Overview.mp4 11.9 MB
  • 14. Appendix Machine Learning Primer/6. Exercise YouTube Recommendation Engine.mp4 11.6 MB
  • 13. Where To Go From Here/1. Thank You!.mp4 11.2 MB
  • 15. Appendix Machine Learning and Data Science Framework/7. Types of Evaluation.mp4 10.1 MB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/5. Discussing the four (actually five) modelling experiments we're running.mp4 9.9 MB
  • 15. Appendix Machine Learning and Data Science Framework/2. Section Overview.mp4 8.0 MB
  • 15. Appendix Machine Learning and Data Science Framework/11. Modelling - Tuning.mp4 7.0 MB
  • 15. Appendix Machine Learning and Data Science Framework/3. Introducing Our Framework.mp4 6.6 MB
  • 16. Appendix Pandas for Data Analysis/2. Section Overview.mp4 6.4 MB
  • 14. Appendix Machine Learning Primer/10. Section Review.mp4 3.6 MB
  • 17. Appendix NumPy/18. Assignment NumPy Practice.html 416.5 kB
  • 17. Appendix NumPy/19. Optional Extra NumPy resources.html 416.2 kB
  • 17. Appendix NumPy/4. Quick Note Correction In Next Video.html 402.9 kB
  • 17. Appendix NumPy/1. Quick Note Upcoming Videos.html 398.9 kB
  • 16. Appendix Pandas for Data Analysis/13. Assignment Pandas Practice.html 398.4 kB
  • 16. Appendix Pandas for Data Analysis/6. Data from URLs.html 391.3 kB
  • 16. Appendix Pandas for Data Analysis/3. Downloading Workbooks and Assignments.html 387.8 kB
  • 16. Appendix Pandas for Data Analysis/1. Quick Note Upcoming Videos.html 385.6 kB
  • 15. Appendix Machine Learning and Data Science Framework/16. Optional Elements of AI(document).html 385.0 kB
  • 15. Appendix Machine Learning and Data Science Framework/13. Overfitting and Underfitting Definitions.html 383.2 kB
  • 15. Appendix Machine Learning and Data Science Framework/1. Quick Note Upcoming Videos.html 370.4 kB
  • 14. Appendix Machine Learning Primer/8. Are You Getting It Yet.html 367.1 kB
  • 13. Where To Go From Here/6. LinkedIn Endorsements.html 361.1 kB
  • 14. Appendix Machine Learning Primer/1. Quick Note Upcoming Videos.html 360.9 kB
  • 13. Where To Go From Here/5. ZTM Events Every Month.html 358.4 kB
  • 13. Where To Go From Here/4. Learning Guideline.html 357.4 kB
  • 13. Where To Go From Here/3. Become An Alumni.html 356.5 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/64. TensorFlow Time Series Fundamentals Challenge and Extra Resources.html 355.9 kB
  • 13. Where To Go From Here/2. Review This Course!.html 355.6 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/1. Welcome to time series fundamentals with TensorFlow + Milestone Project 3!.html 292.9 kB
  • 11. Milestone Project 2 SkimLit/36. Milestone Project 2 (SkimLit) challenge, exercises and extra-curriculum.html 291.9 kB
  • 10. NLP Fundamentals in TensorFlow/35. NLP Fundamentals in TensorFlow challenge, exercises and extra-curriculum.html 256.8 kB
  • 9. Milestone Project 1 Food Vision Big™/16. Milestone Project 1 Food Vision Big™, exercises and extra-curriculum.html 222.3 kB
  • 10. NLP Fundamentals in TensorFlow/1. Welcome to natural language processing with TensorFlow!.html 222.0 kB
  • 9. Milestone Project 1 Food Vision Big™/10. Note Mixed Precision producing errors for TensorFlow 2.5+.html 216.1 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/23. Transfer Learning in TensorFlow Part 3 challenge, exercises and extra-curriculum.html 206.6 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/29. Transfer Learning in TensorFlow Part 2 challenge, exercises and extra-curriculum.html 184.2 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/14. Note Small fix for next video, for images not augmenting.html 168.6 kB
  • 1. Introduction/4.1. All Course Resources + Notebooks.jpg 162.2 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/7. Note Fixes for EfficientNetB0 model creation + weight loading.html 161.5 kB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/11. TensorFlow Transfer Learning Part 1 challenge, exercises & extra-curriculum.html 155.3 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/37. TensorFlow computer vision and CNNs challenge, exercises & extra-curriculum.html 143.7 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/38. Implement a New Life System.html 142.2 kB
  • 4. Neural network classification in TensorFlow/35. TensorFlow classification challenge, exercises & extra-curriculum.html 106.2 kB
  • 4. Neural network classification in TensorFlow/36. Course Check-In.html 104.8 kB
  • 4. Neural network classification in TensorFlow/10. Note Updates for TensorFlow 2.7.0.html 82.5 kB
  • 3. Neural network regression with TensorFlow/31. TensorFlow Regression challenge, exercises & extra-curriculum.html 70.3 kB
  • 3. Neural network regression with TensorFlow/32. Unlimited Updates.html 69.4 kB
  • 3. Neural network regression with TensorFlow/5. Note Code update for upcoming lecture(s) for TensorFlow 2.7.0+ fix.html 45.0 kB
  • 3. Neural network regression with TensorFlow/6. Endorsements On LinkedIn.html 44.9 kB
  • 2. Deep Learning and TensorFlow Fundamentals/30. TensorFlow Fundamentals challenge, exercises & extra-curriculum.html 38.7 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/23. Writing a preprocessing function to turn time series data into windows & labels.en.srt 38.0 kB
  • 2. Deep Learning and TensorFlow Fundamentals/31. Let's Have Some Fun (+ Free Resources).html 37.9 kB
  • 10. NLP Fundamentals in TensorFlow/16. Visualizing our model's learned word embeddings with TensorFlow's projector tool.en.srt 35.2 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/47. Model 7 Putting together the pieces of the puzzle of the N-BEATS model.en.srt 35.1 kB
  • 11. Milestone Project 2 SkimLit/17. Creating a character-level tokeniser with TensorFlow's TextVectorization layer.en.srt 34.0 kB
  • 10. NLP Fundamentals in TensorFlow/15. Model 1 Building, fitting and evaluating our first deep model on text data.en.srt 33.7 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/50. Model 8 Building, compiling and fitting an ensemble of models.en.srt 32.8 kB
  • 10. NLP Fundamentals in TensorFlow/20. Model 4 Building, fitting and evaluating a bidirectional RNN model.en.srt 32.0 kB
  • 10. NLP Fundamentals in TensorFlow/21. Discussing the intuition behind Conv1D neural networks for text and sequences.en.srt 30.7 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/21. Preparing Model 3 (our first fine-tuned model).en.srt 29.9 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/26. Model 1 Building, compiling and fitting a deep learning model on Bitcoin data.en.srt 29.6 kB
  • 3. Neural network regression with TensorFlow/7. The major steps in modelling with TensorFlow.en.srt 29.1 kB
  • 2. Deep Learning and TensorFlow Fundamentals/10. Creating your first tensors with TensorFlow and tf.constant().en.srt 29.0 kB
  • 11. Milestone Project 2 SkimLit/6. Writing a preprocessing function to structure our data for modelling.en.srt 28.9 kB
  • 4. Neural network classification in TensorFlow/19. Using callbacks to find a model's ideal learning rate.en.srt 28.4 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/18. Making predictions on our test images and evaluating them.en.srt 28.4 kB
  • 10. NLP Fundamentals in TensorFlow/19. Model 3 Building, fitting and evaluating a GRU-cell powered RNN.en.srt 28.2 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/17. Building Model 2 (with a data augmentation layer and 10% of training data).en.srt 27.7 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/27. Multi-class CNN's part 1 Becoming one with the data.en.srt 26.8 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/15. Breaking our CNN model down part 5 Looking inside a Conv2D layer.en.srt 26.7 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/51. Model 8 Making and evaluating predictions with our ensemble model.en.srt 26.4 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/28. Model 2 Building, fitting and evaluating a deep model with a larger window size-27.en.srt 26.4 kB
  • 9. Milestone Project 1 Food Vision Big™/5. Exploring and becoming one with the data (Food101 from TensorFlow Datasets).en.srt 26.2 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/4. Downloading and turning our images into a TensorFlow BatchDataset.en.srt 26.2 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/16. Building Model 1 (with a data augmentation layer and 1% of training data).en.srt 26.0 kB
  • 10. NLP Fundamentals in TensorFlow/6. Becoming one with the data and visualizing a text dataset.en.srt 26.0 kB
  • 11. Milestone Project 2 SkimLit/21. Model 4 Building a multi-input model (hybrid token + character embeddings).en.srt 25.9 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/7. Building an end to end CNN Model.en.srt 25.9 kB
  • 10. NLP Fundamentals in TensorFlow/9. Setting up a TensorFlow TextVectorization layer to convert text to numbers.en.srt 25.7 kB
  • 11. Milestone Project 2 SkimLit/1. Introduction to Milestone Project 2 SkimLit.en.srt 25.6 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/42. Model 7 Testing our N-BEATS block implementation with dummy data inputs.en.srt 25.5 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/35. Model 5 Building, fitting and evaluating a LSTM (RNN) model on our Bitcoin data.en.srt 25.3 kB
  • 3. Neural network regression with TensorFlow/13. Evaluating a TensorFlow model part 3 (getting a model summary).en.srt 25.2 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/20. Breaking our CNN model down part 10 Visualizing our augmented data.en.srt 25.2 kB
  • 4. Neural network classification in TensorFlow/27. Multi-class classification part 3 Building a multi-class classification model.en.srt 24.5 kB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/10. Comparing Our Model's Results.en.srt 24.4 kB
  • 4. Neural network classification in TensorFlow/34. What patterns is our model learning.en.srt 24.3 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/8. Downloading and inspecting our Bitcoin historical dataset.en.srt 24.3 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/34. Model 4 Building, fitting and evaluating a Conv1D model on our Bitcoin data.en.srt 23.9 kB
  • 10. NLP Fundamentals in TensorFlow/2. Introduction to Natural Language Processing (NLP) and Sequence Problems.en.srt 23.6 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/41. Model 7 Replicating the N-BEATS basic block with TensorFlow layer subclassing.en.srt 23.4 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/27. Creating a function to make predictions with our trained models.en.srt 23.1 kB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/5. Building and compiling a TensorFlow Hub feature extraction model.en.srt 23.0 kB
  • 11. Milestone Project 2 SkimLit/19. Model 3 Building, fitting and evaluating a Conv1D model on character embeddings.en.srt 22.9 kB
  • 11. Milestone Project 2 SkimLit/4. Setting up our notebook for Milestone Project 2 (getting the data).en.srt 22.9 kB
  • 3. Neural network regression with TensorFlow/27. Putting together what we've learned part 3 (improving our regression model).en.srt 22.8 kB
  • 11. Milestone Project 2 SkimLit/14. Model 1 Building, fitting and evaluating a Conv1D with token embeddings.en.srt 22.7 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/18. Breaking our CNN model down part 8 Reducing overfitting with Max Pooling.en.srt 22.7 kB
  • 4. Neural network classification in TensorFlow/9. Creating a function to view our model's not so good predictions.en.srt 22.5 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/43. Model 7 Creating a performant data pipeline for the N-BEATS model with tf.data.en.srt 22.4 kB
  • 16. Appendix Pandas for Data Analysis/9. Selecting and Viewing Data with Pandas Part 2.en.srt 22.3 kB
  • 10. NLP Fundamentals in TensorFlow/23. Using TensorFlow Hub for pretrained word embeddings (transfer learning for NLP).en.srt 22.3 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/62. Model 10 Building a model to predict on turkey data (why forecasting is BS).en.srt 22.2 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/61. Model 10 Introducing the turkey problem and making data for it.en.srt 22.1 kB
  • 4. Neural network classification in TensorFlow/17. Getting great results in less time by tweaking the learning rate.en.srt 22.0 kB
  • 3. Neural network regression with TensorFlow/25. Putting together what we've learned part 1 (preparing a dataset).en.srt 21.9 kB
  • 10. NLP Fundamentals in TensorFlow/18. Model 2 Building, fitting and evaluating our first TensorFlow RNN model (LSTM).en.srt 21.9 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/15. Evaluating every individual class in our dataset.en.srt 21.9 kB
  • 17. Appendix NumPy/14. Exercise Nut Butter Store Sales.en.srt 21.8 kB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/2. Downloading and preparing data for our first transfer learning model.en.srt 21.7 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/63. Comparing the results of all of our models and discussing where to go next.en.srt 21.7 kB
  • 9. Milestone Project 1 Food Vision Big™/6. Creating a preprocessing function to prepare our data for modelling.en.srt 21.7 kB
  • 11. Milestone Project 2 SkimLit/24. Model 4 Building, fitting and evaluating a hybrid embedding model.en.srt 21.7 kB
  • 4. Neural network classification in TensorFlow/16. Non-linearity part 5 Replicating non-linear activation functions from scratch.en.srt 21.6 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/33. Preparing data for building a Conv1D model.en.srt 21.5 kB
  • 4. Neural network classification in TensorFlow/24. Making our confusion matrix prettier.en.srt 21.5 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/29. Model 3 Building, fitting and evaluating a model with a larger horizon size.en.srt 21.5 kB
  • 11. Milestone Project 2 SkimLit/11. Creating a text vectoriser to map our tokens (text) to numbers.en.srt 21.5 kB
  • 10. NLP Fundamentals in TensorFlow/34. Understanding the concept of the speedscore tradeoff.en.srt 21.5 kB
  • 16. Appendix Pandas for Data Analysis/5. Series, Data Frames and CSVs.en.srt 21.4 kB
  • 11. Milestone Project 2 SkimLit/29. Model 5 Completing the build of a tribrid embedding model for sequences.en.srt 21.3 kB
  • 3. Neural network regression with TensorFlow/26. Putting together what we've learned part 2 (building a regression model).en.srt 21.1 kB
  • 11. Milestone Project 2 SkimLit/8. Turning our target labels into numbers (ML models require numbers).en.srt 21.0 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/55. (Optional) Discussing the types of uncertainty in machine learning.en.srt 20.9 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/10. Getting a feature vector from our trained model.en.srt 20.9 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/45. Model 7 Getting ready for residual connections.en.srt 20.8 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/16. Model 0 Making and visualizing a naive forecast model.en.srt 20.8 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/14. Creating a confusion matrix for our model's 101 different classes.en.srt 20.7 kB
  • 10. NLP Fundamentals in TensorFlow/11. Creating an Embedding layer to turn tokenised text into embedding vectors.en.srt 20.7 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/36. Investigating how to turn our univariate time series into multivariate.en.srt 20.6 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/21. Formatting data Part 2 Creating a function to label our windowed time series.en.srt 20.6 kB
  • 9. Milestone Project 1 Food Vision Big™/12. Creating a feature extraction model capable of using mixed precision training.en.srt 20.6 kB
  • 10. NLP Fundamentals in TensorFlow/28. Comparing all our modelling experiments evaluation metrics.en.srt 20.3 kB
  • 2. Deep Learning and TensorFlow Fundamentals/16. Indexing and expanding tensors.en.srt 20.3 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/2. Getting helper functions ready and downloading data to model.en.srt 20.2 kB
  • 4. Neural network classification in TensorFlow/11. Make our poor classification model work for a regression dataset.en.srt 20.2 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/20. Writing code to uncover our model's most wrong predictions.en.srt 20.2 kB
  • 9. Milestone Project 1 Food Vision Big™/4. Introduction to TensorFlow Datasets (TFDS).en.srt 20.1 kB
  • 11. Milestone Project 2 SkimLit/5. Visualizing examples from the dataset (becoming one with the data).en.srt 20.1 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/17. Breaking our CNN model down part 7 Evaluating our CNN's training curves.en.srt 20.1 kB
  • 3. Neural network regression with TensorFlow/19. Setting up TensorFlow modelling experiments part 1 (start with a simple model).en.srt 19.9 kB
  • 17. Appendix NumPy/9. Manipulating Arrays.en.srt 19.8 kB
  • 2. Deep Learning and TensorFlow Fundamentals/19. Matrix multiplication with tensors part 2.en.srt 19.8 kB
  • 17. Appendix NumPy/5. NumPy DataTypes and Attributes.en.srt 19.8 kB
  • 4. Neural network classification in TensorFlow/31. Multi-class classification part 7 Evaluating our model.en.srt 19.7 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/32. Multi-class CNN's part 6 Trying to fix overfitting by removing layers.en.srt 19.7 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/60. Model 9 Plotting our model's future forecasts.en.srt 19.5 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/7. Unfreezing some layers in our base model to prepare for fine-tuning.en.srt 19.4 kB
  • 11. Milestone Project 2 SkimLit/26. Encoding the line number feature to used with Model 5.en.srt 19.3 kB
  • 3. Neural network regression with TensorFlow/10. Steps in improving a model with TensorFlow part 3.en.srt 19.2 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/33. Multi-class CNN's part 7 Trying to fix overfitting with data augmentation.en.srt 19.2 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/17. Creating a function to load and prepare images for making predictions.en.srt 19.2 kB
  • 2. Deep Learning and TensorFlow Fundamentals/15. Getting information from your tensors (tensor attributes).en.srt 19.2 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/17. Discussing some of the most common time series evaluation metrics.en.srt 19.1 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/13. Building a data augmentation layer to use inside our model.en.srt 19.0 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/9. Compiling and fitting our first Functional API model.en.srt 19.0 kB
  • 4. Neural network classification in TensorFlow/28. Multi-class classification part 4 Improving performance with normalisation.en.srt 19.0 kB
  • 4. Neural network classification in TensorFlow/7. Building a not very good classification model with TensorFlow.en.srt 19.0 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/8. Creating our first model with the TensorFlow Keras Functional API.en.srt 18.8 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/5. Becoming One With Data Part 2.en.srt 18.8 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/27. Comparing our modelling experiment results in TensorBoard.en.srt 18.7 kB
  • 11. Milestone Project 2 SkimLit/16. Model 2 Building, fitting and evaluating a Conv1D model with token embeddings.en.srt 18.7 kB
  • 10. NLP Fundamentals in TensorFlow/24. Model 6 Building, training and evaluating a transfer learning model for NLP.en.srt 18.6 kB
  • 17. Appendix NumPy/13. Dot Product vs Element Wise.en.srt 18.6 kB
  • 3. Neural network regression with TensorFlow/4. Creating sample regression data (so we can model it).en.srt 18.6 kB
  • 3. Neural network regression with TensorFlow/20. Setting up TensorFlow modelling experiments part 2 (increasing complexity).en.srt 18.6 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/11. Making predictions with our trained model on 25,250 test samples.en.srt 18.6 kB
  • 16. Appendix Pandas for Data Analysis/10. Manipulating Data.en.srt 18.6 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/52. Discussing the importance of prediction intervals in forecasting.en.srt 18.5 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/12. Breaking our CNN model down part 2 Preparing to load our data.en.srt 18.5 kB
  • 11. Milestone Project 2 SkimLit/3. SkimLit inputs and outputs.en.srt 18.5 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/26. Making a prediction on a custom image with our trained CNN.en.srt 18.5 kB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/1. What is and why use transfer learning.en.srt 18.3 kB
  • 10. NLP Fundamentals in TensorFlow/10. Mapping the TextVectorization layer to text data and turning it into numbers.en.srt 18.1 kB
  • 9. Milestone Project 1 Food Vision Big™/7. Batching and preparing our datasets (to make them run fast).en.srt 17.9 kB
  • 10. NLP Fundamentals in TensorFlow/29. Uploading our model's training logs to TensorBoard and comparing them.en.srt 17.9 kB
  • 16. Appendix Pandas for Data Analysis/11. Manipulating Data 2.en.srt 17.8 kB
  • 10. NLP Fundamentals in TensorFlow/31. Downloading a pretrained model and preparing data to investigate predictions.en.srt 17.7 kB
  • 11. Milestone Project 2 SkimLit/32. Bringing SkimLit to life!!! (fitting and evaluating Model 5).en.srt 17.7 kB
  • 11. Milestone Project 2 SkimLit/15. Preparing a pretrained embedding layer from TensorFlow Hub for Model 2.en.srt 17.7 kB
  • 4. Neural network classification in TensorFlow/30. Multi-class classification part 6 Finding the ideal learning rate.en.srt 17.7 kB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/9. Different Types of Transfer Learning.en.srt 17.6 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/54. Plotting the prediction intervals of our ensemble model predictions.en.srt 17.6 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/15. Visualizing what happens when images pass through our data augmentation layer.en.srt 17.5 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/25. Preparing our final modelling experiment (Model 4).en.srt 17.5 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/7. Time series forecasting inputs and outputs.en.srt 17.5 kB
  • 10. NLP Fundamentals in TensorFlow/14. Creating a function to track and evaluate our model's results.en.srt 17.5 kB
  • 10. NLP Fundamentals in TensorFlow/25. Preparing subsets of data for model 7 (same as model 6 but 10% of data).en.srt 17.4 kB
  • 2. Deep Learning and TensorFlow Fundamentals/9. Need A Refresher.html 17.4 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/22. Making predictions on and plotting our own custom images.en.srt 17.2 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/26. Fine-tuning Model 4 on 100% of the training data and evaluating its results.en.srt 17.1 kB
  • 16. Appendix Pandas for Data Analysis/12. Manipulating Data 3.en.srt 17.1 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/10. Improving our non-CNN model by adding more layers.en.srt 17.1 kB
  • 10. NLP Fundamentals in TensorFlow/22. Model 5 Building, fitting and evaluating a 1D CNN for text.en.srt 17.1 kB
  • 4. Neural network classification in TensorFlow/5. Creating and viewing classification data to model.en.srt 17.0 kB
  • 2. Deep Learning and TensorFlow Fundamentals/18. Matrix multiplication with tensors part 1.en.srt 17.0 kB
  • 2. Deep Learning and TensorFlow Fundamentals/29. Making sure our tensor operations run really fast on GPUs.en.srt 17.0 kB
  • 16. Appendix Pandas for Data Analysis/8. Selecting and Viewing Data with Pandas.en.srt 16.9 kB
  • 2. Deep Learning and TensorFlow Fundamentals/14. Creating tensors from NumPy arrays.en.srt 16.9 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/37. Creating and plotting a multivariate time series with BTC price and block reward.en.srt 16.8 kB
  • 15. Appendix Machine Learning and Data Science Framework/5. Types of Machine Learning Problems.en.srt 16.8 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/1. Introduction to Computer Vision with TensorFlow.en.srt 16.8 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/22. Breaking our CNN model down part 12 Discovering the power of shuffling data.en.srt 16.7 kB
  • 2. Deep Learning and TensorFlow Fundamentals/3. What are neural networks.en.srt 16.7 kB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/4. Exploring the TensorFlow Hub website for pretrained models.en.srt 16.6 kB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/3. Introducing Callbacks in TensorFlow and making a callback to track our models.en.srt 16.5 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/32. Comparing our modelling experiments so far and discussing autocorrelation.en.srt 16.5 kB
  • 4. Neural network classification in TensorFlow/14. Non-linearity part 3 Upgrading our non-linear model with more layers.en.srt 16.4 kB
  • 3. Neural network regression with TensorFlow/29. Preprocessing data with feature scaling part 2 (normalising our data).en.srt 16.3 kB
  • 4. Neural network classification in TensorFlow/12. Non-linearity part 1 Straight lines and non-straight lines.en.srt 16.3 kB
  • 9. Milestone Project 1 Food Vision Big™/2. Making sure we have access to the right GPU for mixed precision training.en.srt 16.3 kB
  • 16. Appendix Pandas for Data Analysis/7. Describing Data with Pandas.en.srt 16.3 kB
  • 11. Milestone Project 2 SkimLit/35. Congratulations and your challenge before heading to the next module.en.srt 16.2 kB
  • 10. NLP Fundamentals in TensorFlow/27. Fixing our data leakage issue with model 7 and retraining it.en.srt 16.1 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/46. Model 7 Outlining the steps we're going to take to build the N-BEATS model.en.srt 16.1 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/21. Plotting and visualizing the samples our model got most wrong.en.srt 16.1 kB
  • 2. Deep Learning and TensorFlow Fundamentals/2. Why use deep learning.en.srt 16.0 kB
  • 17. Appendix NumPy/8. Viewing Arrays and Matrices.en.srt 15.9 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/38. Preparing our multivariate time series for a model.en.srt 15.9 kB
  • 9. Milestone Project 1 Food Vision Big™/11. Turning on mixed precision training with TensorFlow.en.srt 15.9 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/5. Creating a headless EfficientNetB0 model with data augmentation built in.en.srt 15.9 kB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/6. Blowing our previous models out of the water with transfer learning.en.srt 15.8 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/13. Breaking our CNN model down part 3 Loading our data with ImageDataGenerator.en.srt 15.8 kB
  • 10. NLP Fundamentals in TensorFlow/30. Saving and loading in a trained NLP model with TensorFlow.en.srt 15.8 kB
  • 9. Milestone Project 1 Food Vision Big™/14. Training and evaluating a feature extraction model (Food Vision Big™).en.srt 15.8 kB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/8. Building and training a pre-trained EfficientNet model on our data.en.srt 15.8 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/15. Discussing the various modelling experiments were going to be running.en.srt 15.7 kB
  • 10. NLP Fundamentals in TensorFlow/12. Discussing the various modelling experiments we're going to run.en.srt 15.7 kB
  • 11. Milestone Project 2 SkimLit/30. Visually inspecting the architecture of our tribrid embedding model.en.srt 15.7 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/21. Breaking our CNN model down part 11 Training a CNN model on augmented data.en.srt 15.7 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/31. Model 3 Visualizing the results.en.srt 15.6 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/5. What can be forecast.en.srt 15.5 kB
  • 10. NLP Fundamentals in TensorFlow/17. High-level overview of Recurrent Neural Networks (RNNs) + where to learn more.en.srt 15.5 kB
  • 2. Deep Learning and TensorFlow Fundamentals/4. What is deep learning already being used for.en.srt 15.5 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/39. Model 6 Building, fitting and evaluating a multivariate time series model.en.srt 15.4 kB
  • 3. Neural network regression with TensorFlow/28. Preprocessing data with feature scaling part 1 (what is feature scaling).en.srt 15.4 kB
  • 15. Appendix Machine Learning and Data Science Framework/12. Modelling - Comparison.en.srt 15.4 kB
  • 3. Neural network regression with TensorFlow/21. Comparing and tracking your TensorFlow modelling experiments.en.srt 15.4 kB
  • 10. NLP Fundamentals in TensorFlow/4. The typical architecture of a Recurrent Neural Network (RNN).en.srt 15.3 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/12. Downloading and preparing the data for Model 1 (1 percent of training data).en.srt 15.2 kB
  • 11. Milestone Project 2 SkimLit/13. Creating fast loading dataset with the TensorFlow tf.data API.en.srt 15.1 kB
  • 11. Milestone Project 2 SkimLit/12. Creating a custom token embedding layer with TensorFlow.en.srt 15.0 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/59. Model 9 Creating a function to make forecasts into the future.en.srt 14.9 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/8. Using a GPU to run our CNN model 5x faster.en.srt 14.8 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/44. Model 7 Setting up hyperparameters for the N-BEATS algorithm.en.srt 14.8 kB
  • 10. NLP Fundamentals in TensorFlow/8. Converting text data to numbers using tokenisation and embeddings (overview).en.srt 14.7 kB
  • 2. Deep Learning and TensorFlow Fundamentals/20. Matrix multiplication with tensors part 3.en.srt 14.7 kB
  • 10. NLP Fundamentals in TensorFlow/26. Model 7 Building, training and evaluating a transfer learning model on 10% data.en.srt 14.7 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/3. What is a time series problem and example forecasting problems at Uber.en.srt 14.7 kB
  • 11. Milestone Project 2 SkimLit/10. Preparing our data for deep sequence models.en.srt 14.6 kB
  • 4. Neural network classification in TensorFlow/4. Typical architecture of neural network classification models with TensorFlow.en.srt 14.6 kB
  • 4. Neural network classification in TensorFlow/8. Trying to improve our not very good classification model.en.srt 14.5 kB
  • 10. NLP Fundamentals in TensorFlow/13. Model 0 Building a baseline model to try and improve upon.en.srt 14.5 kB
  • 3. Neural network regression with TensorFlow/23. How to load and use a saved TensorFlow model.en.srt 14.5 kB
  • 11. Milestone Project 2 SkimLit/33. Comparing the performance of all of our modelling experiments.en.srt 14.4 kB
  • 3. Neural network regression with TensorFlow/9. Steps in improving a model with TensorFlow part 2.en.srt 14.4 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/11. Reading in our Bitcoin data with Python's CSV module.en.srt 14.4 kB
  • 4. Neural network classification in TensorFlow/1. Introduction to neural network classification in TensorFlow.en.srt 14.3 kB
  • 2. Deep Learning and TensorFlow Fundamentals/12. Creating random tensors with TensorFlow.en.srt 14.3 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/2. Introduction to Convolutional Neural Networks (CNNs) with TensorFlow.en.srt 14.2 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/24. Turning our windowed time series data into training and test sets.en.srt 14.1 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/8. Fine-tuning our feature extraction model and evaluating its performance.en.srt 14.1 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/25. Writing a helper function to load and preprocessing custom images.en.srt 14.0 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/9. Trying a non-CNN model on our image data.en.srt 14.0 kB
  • 4. Neural network classification in TensorFlow/25. Putting things together with multi-class classification part 1 Getting the data.en.srt 14.0 kB
  • 2. Deep Learning and TensorFlow Fundamentals/5. What is and why use TensorFlow.en.srt 13.9 kB
  • 4. Neural network classification in TensorFlow/15. Non-linearity part 4 Modelling our non-linear data once and for all.en.srt 13.9 kB
  • 11. Milestone Project 2 SkimLit/22. Model 4 Plotting and visually exploring different data inputs.en.srt 13.9 kB
  • 11. Milestone Project 2 SkimLit/2. What we're going to cover in Milestone Project 2 (NLP for medical abstracts).en.srt 13.9 kB
  • 2. Deep Learning and TensorFlow Fundamentals/24. Finding the positional minimum and maximum of a tensor (argmin and argmax).en.srt 13.9 kB
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  • 2. Deep Learning and TensorFlow Fundamentals/13. Shuffling the order of tensors.en.srt 13.8 kB
  • 11. Milestone Project 2 SkimLit/9. Model 0 Creating, fitting and evaluating a baseline model for SkimLit.en.srt 13.8 kB
  • 10. NLP Fundamentals in TensorFlow/32. Visualizing our model's most wrong predictions.en.srt 13.7 kB
  • 4. Neural network classification in TensorFlow/20. Training and evaluating a model with an ideal learning rate.en.srt 13.7 kB
  • 3. Neural network regression with TensorFlow/22. How to save a TensorFlow model.en.srt 13.7 kB
  • 3. Neural network regression with TensorFlow/3. Anatomy and architecture of a neural network regression model.en.srt 13.6 kB
  • 17. Appendix NumPy/10. Manipulating Arrays 2.en.srt 13.6 kB
  • 11. Milestone Project 2 SkimLit/31. Creating multi-level data input pipelines for Model 5 with the tf.data API.en.srt 13.6 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/9. Different kinds of time series patterns & different amounts of feature variables.en.srt 13.6 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/35. Multi-class CNN's part 9 Making predictions with our model on custom images.en.srt 13.5 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/40. Model 7 Discussing what we're going to be doing with the N-BEATS algorithm.en.srt 13.4 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/19. Creating a function to evaluate our model's forecasts with various metrics.en.srt 13.4 kB
  • 4. Neural network classification in TensorFlow/23. Creating our first confusion matrix (to see where our model is getting confused).en.srt 13.4 kB
  • 10. NLP Fundamentals in TensorFlow/33. Making and visualizing predictions on the test dataset.en.srt 13.4 kB
  • 3. Neural network regression with TensorFlow/2. Inputs and outputs of a neural network regression model.en.srt 13.3 kB
  • 4. Neural network classification in TensorFlow/33. Multi-class classification part 9 Visualising random model predictions.en.srt 13.2 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/6. Fitting and evaluating our biggest transfer learning model yet.en.srt 13.2 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/12. Creating train and test splits for time series (the wrong way).en.srt 13.1 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/23. Comparing our model's results before and after fine-tuning.en.srt 13.1 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/29. Multi-class CNN's part 3 Building a multi-class CNN model.en.srt 13.0 kB
  • 3. Neural network regression with TensorFlow/15. Evaluating a TensorFlow model part 5 (visualising a model's predictions).en.srt 13.0 kB
  • 9. Milestone Project 1 Food Vision Big™/15. Introducing your Milestone Project 1 challenge build a model to beat DeepFood.en.srt 13.0 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/56. Model 9 Preparing data to create a model capable of predicting into the future.en.srt 13.0 kB
  • 3. Neural network regression with TensorFlow/1. Introduction to Neural Network Regression with TensorFlow.en.srt 13.0 kB
  • 3. Neural network regression with TensorFlow/12. Evaluating a TensorFlow model part 2 (the three datasets).en.srt 13.0 kB
  • 11. Milestone Project 2 SkimLit/23. Crafting multi-input fast loading tf.data datasets for Model 4.en.srt 13.0 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/14. Creating a plotting function to visualize our time series data.en.srt 13.0 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/30. Adjusting the evaluation function to work for predictions with larger horizons.en.srt 12.8 kB
  • 11. Milestone Project 2 SkimLit/28. Model 5 Building the foundations of a tribrid embedding model.en.srt 12.7 kB
  • 11. Milestone Project 2 SkimLit/7. Performing visual data analysis on our preprocessed text.en.srt 12.6 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/16. Plotting our model's F1-scores for each separate class.en.srt 12.6 kB
  • 3. Neural network regression with TensorFlow/16. Evaluating a TensorFlow model part 6 (common regression evaluation metrics).en.srt 12.6 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/48. Model 7 Plotting the N-BEATS algorithm we've created and admiring its beauty.en.srt 12.5 kB
  • 6. Transfer Learning in TensorFlow Part 1 Feature extraction/7. Plotting the loss curves of our ResNet feature extraction model.en.srt 12.5 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/58. Model 9 Discussing what's required for our model to make future predictions.en.srt 12.4 kB
  • 3. Neural network regression with TensorFlow/30. Preprocessing data with feature scaling part 3 (fitting a model on scaled data).en.srt 12.4 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/11. Breaking our CNN model down part 1 Becoming one with the data.en.srt 12.4 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/3. Downloading an image dataset for our first Food Vision model.en.srt 12.3 kB
  • 17. Appendix NumPy/17. Turn Images Into NumPy Arrays.en.srt 12.3 kB
  • 11. Milestone Project 2 SkimLit/27. Encoding the total lines feature to be used with Model 5.en.srt 12.2 kB
  • 10. NLP Fundamentals in TensorFlow/5. Preparing a notebook for our first NLP with TensorFlow project.en.srt 12.2 kB
  • 11. Milestone Project 2 SkimLit/18. Creating a character-level embedding layer with tf.keras.layers.Embedding.en.srt 12.2 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/14. Breaking our CNN model down part 4 Building a baseline CNN model.en.srt 12.1 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/53. Getting the upper and lower bounds of our prediction intervals.en.srt 12.1 kB
  • 17. Appendix NumPy/6. Creating NumPy Arrays.en.srt 12.1 kB
  • 9. Milestone Project 1 Food Vision Big™/9. Creating modelling callbacks for our feature extraction model.en.srt 12.0 kB
  • 2. Deep Learning and TensorFlow Fundamentals/11. Creating tensors with TensorFlow and tf.Variable().en.srt 12.0 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/25. Creating a modelling checkpoint callback to save our best performing model.en.srt 12.0 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/1. Introduction to Transfer Learning Part 3 Scaling Up.en.srt 11.9 kB
  • 9. Milestone Project 1 Food Vision Big™/13. Checking to see if our model is using mixed precision training layer by layer.en.srt 11.9 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/18. Implementing MASE with TensorFlow.en.copy.srt 11.8 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/18. Implementing MASE with TensorFlow.en.srt 11.8 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/28. Multi-class CNN's part 2 Preparing our data (turning it into tensors).en.srt 11.7 kB
  • 17. Appendix NumPy/7. NumPy Random Seed.en.srt 11.7 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/22. Discussing the use of windows and horizons in time series data.en.srt 11.6 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/22. Fitting and evaluating Model 3 (our first fine-tuned model).en.srt 11.6 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/13. Creating train and test splits for time series (the right way).en.srt 11.6 kB
  • 11. Milestone Project 2 SkimLit/25. Model 5 Adding positional embeddings via feature engineering (overview).en.srt 11.6 kB
  • 17. Appendix NumPy/11. Standard Deviation and Variance.en.srt 11.5 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/1. Introduction to Transfer Learning in TensorFlow Part 2 Fine-tuning.en.srt 11.5 kB
  • 2. Deep Learning and TensorFlow Fundamentals/22. Tensor aggregation (finding the min, max, mean & more).en.srt 11.4 kB
  • 9. Milestone Project 1 Food Vision Big™/8. Exploring what happens when we batch and prefetch our data.en.srt 11.4 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/20. Loading and comparing saved weights to our existing trained Model 2.en.srt 11.4 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/16. Breaking our CNN model down part 6 Compiling and fitting our baseline CNN.en.srt 11.2 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/19. Discussing the benefits of finding your model's most wrong predictions.en.srt 11.2 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/36. Saving and loading our trained CNN model.en.srt 11.2 kB
  • 17. Appendix NumPy/16. Sorting Arrays.en.srt 11.2 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/19. Fitting and evaluating Model 2 (and saving its weights using ModelCheckpoint).en.srt 11.1 kB
  • 3. Neural network regression with TensorFlow/11. Evaluating a TensorFlow model part 1 (visualise, visualise, visualise).en.srt 11.1 kB
  • 4. Neural network classification in TensorFlow/2. Example classification problems (and their inputs and outputs).en.srt 11.0 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/24. Downloading and preparing data for our biggest experiment yet (Model 4).en.srt 11.0 kB
  • 11. Milestone Project 2 SkimLit/34. Saving, loading & testing our best performing model.en.srt 10.9 kB
  • 3. Neural network regression with TensorFlow/14. Evaluating a TensorFlow model part 4 (visualising a model's layers).en.srt 10.9 kB
  • 9. Milestone Project 1 Food Vision Big™/1. Introduction to Milestone Project 1 Food Vision Big™.en.srt 10.9 kB
  • 17. Appendix NumPy/12. Reshape and Transpose.en.srt 10.8 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/19. Breaking our CNN model down part 9 Reducing overfitting with data augmentation.en.srt 10.8 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/9. Saving and loading our trained model.en.srt 10.6 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/10. Downloading a pretrained model to make and evaluate predictions with.en.srt 10.5 kB
  • 16. Appendix Pandas for Data Analysis/14. How To Download The Course Assignments.en.srt 10.5 kB
  • 4. Neural network classification in TensorFlow/21. Introducing more classification evaluation methods.en.srt 10.5 kB
  • 14. Appendix Machine Learning Primer/2. What is Machine Learning.en.srt 10.5 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/18. Creating a ModelCheckpoint to save our model's weights during training.en.srt 10.4 kB
  • 4. Neural network classification in TensorFlow/26. Multi-class classification part 2 Becoming one with the data.en.srt 10.1 kB
  • 4. Neural network classification in TensorFlow/3. Input and output tensors of classification problems.en.srt 10.1 kB
  • 11. Milestone Project 2 SkimLit/20. Discussing how we're going to build Model 4 (character + token embeddings).en.srt 9.9 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/30. Multi-class CNN's part 4 Fitting a multi-class CNN model to the data.en.srt 9.9 kB
  • 4. Neural network classification in TensorFlow/18. Using the TensorFlow History object to plot a model's loss curves.en.srt 9.8 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/2. Importing a script full of helper functions (and saving lots of space).en.srt 9.7 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/4. Example forecasting problems in daily life.en.srt 9.6 kB
  • 2. Deep Learning and TensorFlow Fundamentals/8. How to approach this course.en.srt 9.6 kB
  • 2. Deep Learning and TensorFlow Fundamentals/21. Changing the datatype of tensors.en.srt 9.5 kB
  • 14. Appendix Machine Learning Primer/4. Exercise Machine Learning Playground.en.srt 9.5 kB
  • 3. Neural network regression with TensorFlow/17. Evaluating a TensorFlow regression model part 7 (mean absolute error).en.srt 9.3 kB
  • 3. Neural network regression with TensorFlow/24. (Optional) How to save and download files from Google Colab.en.srt 9.2 kB
  • 4. Neural network classification in TensorFlow/13. Non-linearity part 2 Building our first neural network with non-linearity.en.srt 9.2 kB
  • 15. Appendix Machine Learning and Data Science Framework/9. Modelling - Splitting Data.en.srt 9.1 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/20. Discussing other non-TensorFlow kinds of time series forecasting models.en.srt 9.1 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/3. Outlining the model we're going to build and building a ModelCheckpoint callback.en.srt 8.9 kB
  • 2. Deep Learning and TensorFlow Fundamentals/26. One-hot encoding tensors.en.srt 8.8 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/10. Visualizing our Bitcoin historical data with pandas.en.srt 8.7 kB
  • 10. NLP Fundamentals in TensorFlow/7. Splitting data into training and validation sets.en.srt 8.7 kB
  • 17. Appendix NumPy/3. NumPy Introduction.en.srt 8.6 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/12. Unravelling our test dataset for comparing ground truth labels to predictions.en.srt 8.5 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/23. Breaking our CNN model down part 13 Exploring options to improve our model.en.srt 8.5 kB
  • 14. Appendix Machine Learning Primer/5. How Did We Get Here.en.srt 8.5 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/24. Downloading a custom image to make predictions on.en.srt 8.5 kB
  • 2. Deep Learning and TensorFlow Fundamentals/7. What we're going to cover throughout the course.en.srt 8.3 kB
  • 4. Neural network classification in TensorFlow/6. Checking the input and output shapes of our classification data.en.srt 8.2 kB
  • 2. Deep Learning and TensorFlow Fundamentals/28. Exploring TensorFlow and NumPy's compatibility.en.srt 8.1 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/57. Model 9 Building, compiling and fitting a future predictions model.en.srt 8.0 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/31. Multi-class CNN's part 5 Evaluating our multi-class CNN model.en.srt 8.0 kB
  • 1. Introduction/7. Set Your Learning Streak Goal.html 8.0 kB
  • 15. Appendix Machine Learning and Data Science Framework/8. Features In Data.en.srt 7.9 kB
  • 15. Appendix Machine Learning and Data Science Framework/4. 6 Step Machine Learning Framework.en.srt 7.9 kB
  • 16. Appendix Pandas for Data Analysis/4. Pandas Introduction.en.srt 7.9 kB
  • 2. Deep Learning and TensorFlow Fundamentals/23. Tensor troubleshooting example (updating tensor datatypes).en.srt 7.8 kB
  • 2. Deep Learning and TensorFlow Fundamentals/1. What is deep learning.en.srt 7.8 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/13. Confirming our model's predictions are in the same order as the test labels.en.srt 7.8 kB
  • 3. Neural network regression with TensorFlow/8. Steps in improving a model with TensorFlow part 1.en.srt 7.7 kB
  • 2. Deep Learning and TensorFlow Fundamentals/17. Manipulating tensors with basic operations.en.srt 7.7 kB
  • 15. Appendix Machine Learning and Data Science Framework/10. Modelling - Picking the Model.en.srt 7.6 kB
  • 4. Neural network classification in TensorFlow/32. Multi-class classification part 8 Creating a confusion matrix.en.srt 7.5 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/49. Model 8 Ensemble model overview.en.srt 7.5 kB
  • 1. Introduction/4. All Course Resources + Notebooks.html 7.5 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/2. Introduction to Milestone Project 3 (BitPredict) & where you can get help.en.srt 7.5 kB
  • 14. Appendix Machine Learning Primer/3. AIMachine LearningData Science.en.srt 7.4 kB
  • 8. Transfer Learning with TensorFlow Part 3 Scaling Up/4. Creating a data augmentation layer to use with our model.en.srt 7.4 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/6. Becoming One With Data Part 3.en.srt 7.3 kB
  • 1. Introduction/2. Course Outline.en.srt 7.2 kB
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  • 14. Appendix Machine Learning Primer/9. What Is Machine Learning Round 2.en.srt 7.1 kB
  • 5. Computer Vision and Convolutional Neural Networks in TensorFlow/34. Multi-class CNN's part 8 Things you could do to improve your CNN model.en.srt 7.1 kB
  • 1. Introduction/6. ZTM Plugin + Understanding Your Video Player.html 7.1 kB
  • 4. Neural network classification in TensorFlow/22. Finding the accuracy of our classification model.en.srt 6.8 kB
  • 15. Appendix Machine Learning and Data Science Framework/15. Tools We Will Use.en.srt 6.8 kB
  • 1. Introduction/5. Python + Machine Learning Monthly.html 6.7 kB
  • 14. Appendix Machine Learning Primer/7. Types of Machine Learning.en.srt 6.6 kB
  • 14. Appendix Machine Learning Primer/6. Exercise YouTube Recommendation Engine.en.srt 6.5 kB
  • 4. Neural network classification in TensorFlow/29. Multi-class classification part 5 Comparing normalised and non-normalised data.en.srt 6.5 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/11. Drilling into the concept of a feature vector (a learned representation).en.srt 6.1 kB
  • 2. Deep Learning and TensorFlow Fundamentals/27. Trying out more tensor math operations.en.srt 6.0 kB
  • 15. Appendix Machine Learning and Data Science Framework/14. Experimentation.en.srt 6.0 kB
  • 15. Appendix Machine Learning and Data Science Framework/11. Modelling - Tuning.en.srt 5.8 kB
  • 2. Deep Learning and TensorFlow Fundamentals/6. What is a Tensor.en.srt 5.8 kB
  • 17. Appendix NumPy/15. Comparison Operators.en.srt 5.6 kB
  • 12. Time Series fundamentals in TensorFlow + Milestone Project 3 BitPredict/6. What we're going to cover (broadly).en.srt 5.4 kB
  • 15. Appendix Machine Learning and Data Science Framework/2. Section Overview.en.srt 5.4 kB
  • 15. Appendix Machine Learning and Data Science Framework/7. Types of Evaluation.en.srt 5.3 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/3. Exercise Imposter Syndrome.en.srt 4.9 kB
  • 9. Milestone Project 1 Food Vision Big™/3. Getting helper functions ready.en.srt 4.7 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/6. Comparing the TensorFlow Keras Sequential API versus the Functional API.en.srt 4.6 kB
  • 1. Introduction/3. Exercise Meet Your Classmates and Instructor.html 4.5 kB
  • 2. Deep Learning and TensorFlow Fundamentals/25. Squeezing a tensor (removing all 1-dimension axes).en.srt 4.4 kB
  • 3. Neural network regression with TensorFlow/18. Evaluating a TensorFlow regression model part 7 (mean square error).en.srt 4.4 kB
  • 15. Appendix Machine Learning and Data Science Framework/3. Introducing Our Framework.en.srt 4.1 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/5. Discussing the four (actually five) modelling experiments we're running.en.srt 4.0 kB
  • 17. Appendix NumPy/2. Section Overview.en.srt 3.9 kB
  • 16. Appendix Pandas for Data Analysis/2. Section Overview.en.srt 3.9 kB
  • 7. Transfer Learning in TensorFlow Part 2 Fine tuning/28. How to view and delete previous TensorBoard experiments.en.srt 3.4 kB
  • 14. Appendix Machine Learning Primer/10. Section Review.en.srt 2.7 kB
  • 1. Introduction/1. TensorFlow for Deep Learning Zero to Mastery.en.srt 2.5 kB
  • 13. Where To Go From Here/1. Thank You!.en.srt 2.0 kB
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