Udemy - [2025] Tensorflow 2 Deep Learning & Artificial Intelligence (1.2025)

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Udemy - [2025] Tensorflow 2 Deep Learning & Artificial Intelligence (1.2025)

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种子哈希：32a46c64dfa1f6f0218edb893777f926905fd602
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收录时间：2025-08-10
最近下载：2025-09-29

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文件列表

  • 8 - Natural Language Processing (NLP)/4 -Text Classification with LSTMs.mp4 372.2 MB
  • 20 - Setting up your Environment (FAQ by Student Request)/3 -Anaconda Environment Setup.mp4 365.5 MB
  • 8 - Natural Language Processing (NLP)/6 -Text Classification with CNNs.mp4 330.7 MB
  • 10 - Transfer Learning for Computer Vision/7 -Transfer Learning Code (pt 1).mp4 321.2 MB
  • 10 - Transfer Learning for Computer Vision/8 -Transfer Learning Code (pt 2).mp4 313.2 MB
  • 3 - Machine Learning and Neurons/5 -Regression Notebook.mp4 259.7 MB
  • 6 - Convolutional Neural Networks/11 -Improving CIFAR-10 Results.mp4 254.3 MB
  • 20 - Setting up your Environment (FAQ by Student Request)/4 -Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4 227.1 MB
  • 20 - Setting up your Environment (FAQ by Student Request)/2 -How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 220.3 MB
  • 3 - Machine Learning and Neurons/3 -Classification Notebook.mp4 193.8 MB
  • 8 - Natural Language Processing (NLP)/3 -Text Preprocessing.mp4 184.0 MB
  • 14 - Advanced Tensorflow Usage/2 -Tensorflow Serving pt 2.mp4 181.2 MB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/12 -Demo of the Long Distance Problem.mp4 165.6 MB
  • 22 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4 -Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 157.1 MB
  • 22 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3 -Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 154.6 MB
  • 5 - Interlude tf.data/2 -Sample Code for tf.data.mp4 154.2 MB
  • 18 - Course Conclusion/2 -What to Learn Next.mp4 148.2 MB
  • 21 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/6 -Proof that using Jupyter Notebook is the same as not using it.mp4 124.8 MB
  • 2 - Google Colab/3 -Uploading your own data to Google Colab.mp4 119.2 MB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/17 -Stock Return Predictions using LSTMs (pt 3).mp4 114.5 MB
  • 4 - Feedforward Artificial Neural Networks/11 -ANN for Regression.mp4 114.2 MB
  • 21 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/4 -How to Code Yourself (part 1).mp4 108.7 MB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/7 -RNN for Time Series Prediction.mp4 99.6 MB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/3 -Autoregressive Linear Model for Time Series Prediction.mp4 99.0 MB
  • 10 - Transfer Learning for Computer Vision/5 -Transfer Learning Code (pt 1) (Legacy).mp4 91.1 MB
  • 13 - Stock Trading Project with Deep Reinforcement Learning/8 -Code pt 4.mp4 90.8 MB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/15 -Stock Return Predictions using LSTMs (pt 1).mp4 89.9 MB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/8 -Paying Attention to Shapes.mp4 87.8 MB
  • 2 - Google Colab/1 -Intro to Google Colab, how to use a GPU or TPU for free.mp4 87.3 MB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/11 -A More Challenging Sequence.mp4 86.5 MB
  • 14 - Advanced Tensorflow Usage/6 -Using the TPU.mp4 82.6 MB
  • 9 - Recommender Systems/2 -Recommender Systems with Deep Learning Code.mp4 81.8 MB
  • 11 - GANs (Generative Adversarial Networks)/2 -GAN Code.mp4 81.6 MB
  • 22 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/5 -Common Beginner Questions What if I'm advanced.mp4 81.0 MB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/1 -Sequence Data.mp4 78.8 MB
  • 13 - Stock Trading Project with Deep Reinforcement Learning/7 -Code pt 3.mp4 75.4 MB
  • 10 - Transfer Learning for Computer Vision/1 -Transfer Learning Theory.mp4 75.2 MB
  • 11 - GANs (Generative Adversarial Networks)/1 -GAN Theory.mp4 74.1 MB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/9 -GRU and LSTM (pt 1).mp4 73.8 MB
  • 22 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2 -Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 72.5 MB
  • 12 - Deep Reinforcement Learning (Theory)/2 -Elements of a Reinforcement Learning Problem.mp4 71.8 MB
  • 6 - Convolutional Neural Networks/5 -CNN Architecture.mp4 71.6 MB
  • 2 - Google Colab/2 -Tensorflow 2 in Google Colab.mp4 70.3 MB
  • 4 - Feedforward Artificial Neural Networks/10 -ANN for Image Classification.mp4 68.2 MB
  • 6 - Convolutional Neural Networks/6 -CNN Code Preparation.mp4 68.1 MB
  • 9 - Recommender Systems/1 -Recommender Systems with Deep Learning Theory.mp4 66.3 MB
  • 13 - Stock Trading Project with Deep Reinforcement Learning/6 -Code pt 2.mp4 64.0 MB
  • 10 - Transfer Learning for Computer Vision/6 -Transfer Learning Code (pt 2) (Legacy).mp4 63.3 MB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/5 -Recurrent Neural Networks.mp4 63.0 MB
  • 4 - Feedforward Artificial Neural Networks/2 -Beginners Rejoice The Math in This Course is Optional.mp4 61.3 MB
  • 15 - Low-Level Tensorflow/4 -Build Your Own Custom Model.mp4 61.0 MB
  • 15 - Low-Level Tensorflow/3 -Variables and Gradient Tape.mp4 60.1 MB
  • 6 - Convolutional Neural Networks/7 -CNN for Fashion MNIST.mp4 59.8 MB
  • 4 - Feedforward Artificial Neural Networks/5 -Activation Functions.mp4 59.8 MB
  • 21 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/2 -How to use Github & Extra Coding Tips (Optional).mp4 59.2 MB
  • 14 - Advanced Tensorflow Usage/5 -Training with Distributed Strategies.mp4 58.0 MB
  • 13 - Stock Trading Project with Deep Reinforcement Learning/5 -Code pt 1.mp4 57.7 MB
  • 3 - Machine Learning and Neurons/1 -What is Machine Learning.mp4 57.3 MB
  • 18 - Course Conclusion/1 -How to get the Tensorflow Developer Certificate.mp4 55.2 MB
  • 8 - Natural Language Processing (NLP)/2 -Code Preparation (NLP).mp4 55.2 MB
  • 6 - Convolutional Neural Networks/4 -Convolution on Color Images.mp4 54.9 MB
  • 15 - Low-Level Tensorflow/2 -Constants and Basic Computation.mp4 52.6 MB
  • 6 - Convolutional Neural Networks/1 -What is Convolution (part 1).mp4 52.4 MB
  • 4 - Feedforward Artificial Neural Networks/7 -How to Represent Images.mp4 51.2 MB
  • 21 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/3 -Beginner's Coding Tips.mp4 51.1 MB
  • 17 - In-Depth Gradient Descent/5 -Adam (pt 1).mp4 50.9 MB
  • 3 - Machine Learning and Neurons/9 -Saving and Loading a Model.mp4 49.4 MB
  • 23 - Appendix FAQ Finale/2 -BONUS.mp4 48.7 MB
  • 1 - Welcome/2 -Outline.mp4 47.3 MB
  • 12 - Deep Reinforcement Learning (Theory)/14 -How to Learn Reinforcement Learning.mp4 46.3 MB
  • 12 - Deep Reinforcement Learning (Theory)/9 -Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4 46.3 MB
  • 12 - Deep Reinforcement Learning (Theory)/11 -Q-Learning.mp4 46.0 MB
  • 3 - Machine Learning and Neurons/11 -Suggestion Box.mp4 45.6 MB
  • 17 - In-Depth Gradient Descent/6 -Adam (pt 2).mp4 44.3 MB
  • 2 - Google Colab/4 -Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.mp4 43.9 MB
  • 12 - Deep Reinforcement Learning (Theory)/12 -Deep Q-Learning DQN (pt 1).mp4 42.5 MB
  • 8 - Natural Language Processing (NLP)/1 -Embeddings.mp4 39.7 MB
  • 13 - Stock Trading Project with Deep Reinforcement Learning/2 -Data and Environment.mp4 39.6 MB
  • 4 - Feedforward Artificial Neural Networks/9 -Code Preparation (ANN).mp4 39.0 MB
  • 12 - Deep Reinforcement Learning (Theory)/13 -Deep Q-Learning DQN (pt 2).mp4 36.8 MB
  • 3 - Machine Learning and Neurons/7 -How does a model learn.mp4 36.6 MB
  • 4 - Feedforward Artificial Neural Networks/6 -Multiclass Classification.mp4 36.5 MB
  • 14 - Advanced Tensorflow Usage/3 -Tensorflow Lite (TFLite).mp4 36.4 MB
  • 12 - Deep Reinforcement Learning (Theory)/1 -Deep Reinforcement Learning Section Introduction.mp4 36.0 MB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/10 -GRU and LSTM (pt 2).mp4 35.4 MB
  • 21 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/5 -How to Code Yourself (part 2).mp4 35.0 MB
  • 12 - Deep Reinforcement Learning (Theory)/4 -Markov Decision Processes (MDPs).mp4 34.8 MB
  • 13 - Stock Trading Project with Deep Reinforcement Learning/10 -Help! Why is the code slower on my machine.mp4 34.6 MB
  • 4 - Feedforward Artificial Neural Networks/4 -The Geometrical Picture.mp4 34.4 MB
  • 3 - Machine Learning and Neurons/8 -Making Predictions.mp4 34.4 MB
  • 3 - Machine Learning and Neurons/6 -The Neuron.mp4 32.7 MB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/16 -Stock Return Predictions using LSTMs (pt 2).mp4 32.2 MB
  • 14 - Advanced Tensorflow Usage/4 -Why is Google the King of Distributed Computing.mp4 32.1 MB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/2 -Forecasting.mp4 31.8 MB
  • 12 - Deep Reinforcement Learning (Theory)/6 -Value Functions and the Bellman Equation.mp4 31.5 MB
  • 2 - Google Colab/6 -Temporary 403 Errors.mp4 31.3 MB
  • 12 - Deep Reinforcement Learning (Theory)/8 -Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4 31.3 MB
  • 4 - Feedforward Artificial Neural Networks/3 -Forward Propagation.mp4 30.9 MB
  • 12 - Deep Reinforcement Learning (Theory)/3 -States, Actions, Rewards, Policies.mp4 30.8 MB
  • 21 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/1 -Get Your Hands Dirty, Practical Coding Experience, Data Links.mp4 30.3 MB
  • 17 - In-Depth Gradient Descent/3 -Momentum.mp4 30.1 MB
  • 1 - Welcome/1 -Introduction.mp4 29.5 MB
  • 15 - Low-Level Tensorflow/1 -Differences Between Tensorflow 1.x and Tensorflow 2.x.mp4 29.2 MB
  • 17 - In-Depth Gradient Descent/4 -Variable and Adaptive Learning Rates.mp4 28.8 MB
  • 22 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/1 -How to Succeed in this Course (Long Version).mp4 28.7 MB
  • 10 - Transfer Learning for Computer Vision/2 -Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).mp4 28.2 MB
  • 21 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/7 -Is Theano Dead.mp4 28.1 MB
  • 10 - Transfer Learning for Computer Vision/3 -Large Datasets and Data Generators.mp4 27.0 MB
  • 6 - Convolutional Neural Networks/9 -Data Augmentation.mp4 26.9 MB
  • 12 - Deep Reinforcement Learning (Theory)/10 -Epsilon-Greedy.mp4 26.7 MB
  • 8 - Natural Language Processing (NLP)/5 -CNNs for Text.mp4 26.0 MB
  • 16 - In-Depth Loss Functions/1 -Mean Squared Error.mp4 25.4 MB
  • 17 - In-Depth Gradient Descent/1 -Gradient Descent.mp4 25.0 MB
  • 19 - Extras/1 -How to Choose Hyperparameters.mp4 25.0 MB
  • 3 - Machine Learning and Neurons/10 -Why Keras.mp4 23.8 MB
  • 16 - In-Depth Loss Functions/3 -Categorical Cross Entropy.mp4 23.7 MB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/14 -RNN for Image Classification (Code).mp4 23.2 MB
  • 12 - Deep Reinforcement Learning (Theory)/7 -What does it mean to “learn”.mp4 22.8 MB
  • 4 - Feedforward Artificial Neural Networks/1 -Artificial Neural Networks Section Introduction.mp4 22.0 MB
  • 17 - In-Depth Gradient Descent/2 -Stochastic Gradient Descent.mp4 21.5 MB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/13 -RNN for Image Classification (Theory).mp4 21.5 MB
  • 1 - Welcome/3 -Where to get the code, notebooks, and data.mp4 21.4 MB
  • 6 - Convolutional Neural Networks/8 -CNN for CIFAR-10.mp4 21.0 MB
  • 3 - Machine Learning and Neurons/4 -Code Preparation (Regression Theory).mp4 20.8 MB
  • 19 - Extras/2 -Get the Exercise Pack for This Course.mp4 20.6 MB
  • 14 - Advanced Tensorflow Usage/1 -What is a Web Service (Tensorflow Serving pt 1).mp4 20.4 MB
  • 6 - Convolutional Neural Networks/3 -What is Convolution (part 3).mp4 20.2 MB
  • 13 - Stock Trading Project with Deep Reinforcement Learning/4 -Program Design and Layout.mp4 19.6 MB
  • 13 - Stock Trading Project with Deep Reinforcement Learning/1 -Reinforcement Learning Stock Trader Introduction.mp4 19.4 MB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/18 -Other Ways to Forecast.mp4 19.0 MB
  • 10 - Transfer Learning for Computer Vision/4 -2 Approaches to Transfer Learning.mp4 18.2 MB
  • 6 - Convolutional Neural Networks/2 -What is Convolution (part 2).mp4 17.5 MB
  • 13 - Stock Trading Project with Deep Reinforcement Learning/3 -Replay Buffer.mp4 17.4 MB
  • 6 - Convolutional Neural Networks/10 -Batch Normalization.mp4 15.8 MB
  • 20 - Setting up your Environment (FAQ by Student Request)/1 -Pre-Installation Check.mp4 15.8 MB
  • 16 - In-Depth Loss Functions/2 -Binary Cross Entropy.mp4 15.7 MB
  • 12 - Deep Reinforcement Learning (Theory)/5 -The Return.mp4 15.6 MB
  • 5 - Interlude tf.data/1 -Why use tf.data.mp4 14.4 MB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/6 -RNN Code Preparation.mp4 14.3 MB
  • 2 - Google Colab/7 -Course Updates.mp4 12.2 MB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/4 -Proof that the Linear Model Works.mp4 12.0 MB
  • 13 - Stock Trading Project with Deep Reinforcement Learning/9 -Reinforcement Learning Stock Trader Discussion.mp4 11.7 MB
  • 2 - Google Colab/5 -How to Succeed in This Course.mp4 10.9 MB
  • 23 - Appendix FAQ Finale/1 -What is the Appendix.mp4 10.6 MB
  • 4 - Feedforward Artificial Neural Networks/8 -Color Mixing Clarification.mp4 3.2 MB
  • 8 - Natural Language Processing (NLP)/subtitles/4 -Text Classification with LSTMs.ko_KR.vtt 32.5 kB
  • 3 - Machine Learning and Neurons/subtitles/5 -Regression Notebook.es_ES.vtt 32.0 kB
  • 20 - Setting up your Environment (FAQ by Student Request)/subtitles/4 -Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.es_ES.vtt 30.5 kB
  • 3 - Machine Learning and Neurons/5 -Regression Notebook.vtt 30.3 kB
  • 8 - Natural Language Processing (NLP)/subtitles/4 -Text Classification with LSTMs.es_ES.vtt 30.0 kB
  • 22 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/2 -Is this for Beginners or Experts Academic or Practical Fast or slow-paced.es_ES.vtt 29.6 kB
  • 8 - Natural Language Processing (NLP)/subtitles/6 -Text Classification with CNNs.ko_KR.vtt 29.5 kB
  • 22 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/5 -Common Beginner Questions What if I'm advanced.es_ES.vtt 29.3 kB
  • 3 - Machine Learning and Neurons/subtitles/5 -Regression Notebook.ko_KR.vtt 29.2 kB
  • 20 - Setting up your Environment (FAQ by Student Request)/subtitles/4 -Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.ko_KR.vtt 29.1 kB
  • 22 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/5 -Common Beginner Questions What if I'm advanced.vtt 28.6 kB
  • 20 - Setting up your Environment (FAQ by Student Request)/4 -Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.vtt 28.6 kB
  • 22 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2 -Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 28.3 kB
  • 10 - Transfer Learning for Computer Vision/subtitles/8 -Transfer Learning Code (pt 2).es_ES.vtt 27.9 kB
  • 22 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/2 -Is this for Beginners or Experts Academic or Practical Fast or slow-paced.ko_KR.vtt 27.8 kB
  • 10 - Transfer Learning for Computer Vision/subtitles/7 -Transfer Learning Code (pt 1).es_ES.vtt 27.7 kB
  • 8 - Natural Language Processing (NLP)/4 -Text Classification with LSTMs.vtt 27.5 kB
  • 8 - Natural Language Processing (NLP)/subtitles/6 -Text Classification with CNNs.es_ES.vtt 27.3 kB
  • 6 - Convolutional Neural Networks/subtitles/5 -CNN Architecture.es_ES.vtt 27.2 kB
  • 22 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/5 -Common Beginner Questions What if I'm advanced.ko_KR.vtt 27.0 kB
  • 10 - Transfer Learning for Computer Vision/8 -Transfer Learning Code (pt 2).vtt 25.8 kB
  • 10 - Transfer Learning for Computer Vision/7 -Transfer Learning Code (pt 1).vtt 25.7 kB
  • 3 - Machine Learning and Neurons/subtitles/3 -Classification Notebook.es_ES.vtt 25.6 kB
  • 10 - Transfer Learning for Computer Vision/subtitles/8 -Transfer Learning Code (pt 2).ko_KR.vtt 25.4 kB
  • 10 - Transfer Learning for Computer Vision/subtitles/7 -Transfer Learning Code (pt 1).ko_KR.vtt 25.2 kB
  • 5 - Interlude tf.data/subtitles/2 -Sample Code for tf.data.es_ES.vtt 25.2 kB
  • 8 - Natural Language Processing (NLP)/6 -Text Classification with CNNs.vtt 25.1 kB
  • 6 - Convolutional Neural Networks/5 -CNN Architecture.vtt 25.0 kB
  • 12 - Deep Reinforcement Learning (Theory)/subtitles/2 -Elements of a Reinforcement Learning Problem.es_ES.vtt 24.8 kB
  • 6 - Convolutional Neural Networks/subtitles/5 -CNN Architecture.ko_KR.vtt 24.8 kB
  • 8 - Natural Language Processing (NLP)/subtitles/3 -Text Preprocessing.ko_KR.vtt 24.7 kB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/subtitles/5 -Recurrent Neural Networks.es_ES.vtt 24.2 kB
  • 3 - Machine Learning and Neurons/3 -Classification Notebook.vtt 24.1 kB
  • 3 - Machine Learning and Neurons/subtitles/3 -Classification Notebook.ko_KR.vtt 23.6 kB
  • 12 - Deep Reinforcement Learning (Theory)/subtitles/2 -Elements of a Reinforcement Learning Problem.ko_KR.vtt 23.5 kB
  • 12 - Deep Reinforcement Learning (Theory)/2 -Elements of a Reinforcement Learning Problem.vtt 23.4 kB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/subtitles/1 -Sequence Data.es_ES.vtt 23.2 kB
  • 5 - Interlude tf.data/2 -Sample Code for tf.data.vtt 23.1 kB
  • 8 - Natural Language Processing (NLP)/subtitles/3 -Text Preprocessing.es_ES.vtt 23.0 kB
  • 5 - Interlude tf.data/subtitles/2 -Sample Code for tf.data.ko_KR.vtt 22.9 kB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/5 -Recurrent Neural Networks.vtt 22.8 kB
  • 22 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/4 -Machine Learning and AI Prerequisite Roadmap (pt 2).es_ES.vtt 22.7 kB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/subtitles/12 -Demo of the Long Distance Problem.es_ES.vtt 22.2 kB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/subtitles/5 -Recurrent Neural Networks.ko_KR.vtt 22.0 kB
  • 6 - Convolutional Neural Networks/subtitles/11 -Improving CIFAR-10 Results.es_ES.vtt 21.9 kB
  • 4 - Feedforward Artificial Neural Networks/subtitles/5 -Activation Functions.es_ES.vtt 21.5 kB
  • 18 - Course Conclusion/subtitles/1 -How to get the Tensorflow Developer Certificate.es_ES.vtt 21.5 kB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/subtitles/9 -GRU and LSTM (pt 1).es_ES.vtt 21.4 kB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/1 -Sequence Data.vtt 21.4 kB
  • 8 - Natural Language Processing (NLP)/3 -Text Preprocessing.vtt 21.3 kB
  • 21 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/subtitles/4 -How to Code Yourself (part 1).es_ES.vtt 21.1 kB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/subtitles/1 -Sequence Data.ko_KR.vtt 20.9 kB
  • 22 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4 -Machine Learning and AI Prerequisite Roadmap (pt 2).vtt 20.7 kB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/12 -Demo of the Long Distance Problem.vtt 20.6 kB
  • 22 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/4 -Machine Learning and AI Prerequisite Roadmap (pt 2).ko_KR.vtt 20.5 kB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/9 -GRU and LSTM (pt 1).vtt 20.4 kB
  • 4 - Feedforward Artificial Neural Networks/5 -Activation Functions.vtt 20.3 kB
  • 6 - Convolutional Neural Networks/11 -Improving CIFAR-10 Results.vtt 20.2 kB
  • 6 - Convolutional Neural Networks/subtitles/4 -Convolution on Color Images.es_ES.vtt 20.2 kB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/subtitles/12 -Demo of the Long Distance Problem.ko_KR.vtt 19.9 kB
  • 18 - Course Conclusion/subtitles/1 -How to get the Tensorflow Developer Certificate.ko_KR.vtt 19.9 kB
  • 21 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/4 -How to Code Yourself (part 1).vtt 19.8 kB
  • 14 - Advanced Tensorflow Usage/subtitles/2 -Tensorflow Serving pt 2.es_ES.vtt 19.8 kB
  • 6 - Convolutional Neural Networks/subtitles/11 -Improving CIFAR-10 Results.ko_KR.vtt 19.8 kB
  • 18 - Course Conclusion/subtitles/2 -What to Learn Next.es_ES.vtt 19.7 kB
  • 4 - Feedforward Artificial Neural Networks/subtitles/5 -Activation Functions.ko_KR.vtt 19.6 kB
  • 7 - Recurrent Neural Networks, Time Series, and Sequence Data/subtitles/9 -GRU and LSTM (pt 1).ko_KR.vtt 19.6 kB
  • 3 - Machine Learning and Neurons/subtitles/2 -Code Preparation (Classification Theory).es_ES.vtt 19.5 kB
  • 6 - Convolutional Neural Networks/subtitles/1 -What is Convolution (part 1).es_ES.vtt 19.5 kB
  • 11 - GANs (Generative Adversarial Networks)/subtitles/1 -GAN Theory.es_ES.vtt 19.4 kB
  • 20 - Setting up your Environment (FAQ by Student Request)/subtitles/3 -Anaconda Environment Setup.es_ES.vtt 19.4 kB
  • 21 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/subtitles/4 -How to Code Yourself (part 1).ko_KR.vtt 19.4 kB
  • 18 - Course Conclusion/1 -How to get the Tensorflow Developer Certificate.vtt 19.3 kB
  • 8 - Natural Language Processing (NLP)/subtitles/2 -Code Preparation (NLP).ko_KR.vtt 18.9 kB
  • 6 - Convolutional Neural Networks/subtitles/6 -CNN Code Preparation.es_ES.vtt 18.8 kB
  • 6 - Convolutional Neural Networks/4 -Convolution on Color Images.vtt 18.8 kB
  • 11 - GANs (Generative Adversarial Networks)/1 -GAN Theory.vtt 18.5 kB
  • 20 - Setting up your Environment (FAQ by Student Request)/subtitles/3 -Anaconda Environment Setup.ko_KR.vtt 18.3 kB
  • 14 - Advanced Tensorflow Usage/2 -Tensorflow Serving pt 2.vtt 18.2 kB
  • 3 - Machine Learning and Neurons/2 -Code Preparation (Classification Theory).vtt 18.2 kB
  • 6 - Convolutional Neural Networks/subtitles/1 -What is Convolution (part 1).ko_KR.vtt 18.2 kB
  • 18 - Course Conclusion/2 -What to Learn Next.vtt 18.2 kB
  • 6 - Convolutional Neural Networks/subtitles/4 -Convolution on Color Images.ko_KR.vtt 18.1 kB
  • 11 - GANs (Generative Adversarial Networks)/subtitles/1 -GAN Theory.ko_KR.vtt 18.1 kB
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  • 3 - Machine Learning and Neurons/subtitles/8 -Making Predictions.es_ES.vtt 7.9 kB
  • 23 - Appendix FAQ Finale/subtitles/2 -BONUS.es_ES.vtt 7.9 kB
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  • 1 - Welcome/3 -Data Links.url 119 Bytes
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  • 21 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/1 -Github Links.url 100 Bytes
  • 1 - Welcome/3 -Code Link.url 87 Bytes

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