Udemy - Deep Learning Masterclass with TensorFlow 2 Over 20 Projects (4.2024)

磁力链接/BT种子名称

Udemy - Deep Learning Masterclass with TensorFlow 2 Over 20 Projects (4.2024)

磁力链接/BT种子简介

种子哈希：beefc2e4add01047324c7cd8f02166bd787096cc
文件大小： 27.41G
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收录时间：2025-07-25
最近下载：2025-10-21

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文件列表

  • 19. Object Detection with YOLO algorithm/06. YOLO Loss.mp4 695.8 MB
  • 18. Model deployment/07. Building the Emotions Detection API with Fastapi.mp4 679.0 MB
  • 34. Extractive Question Answering with Longformer in Huggingface transformers/02. Problem Understanding and Data Preparation.mp4 618.5 MB
  • 28. Neural Machine Translation with Transformers/02. Understanding Transformer Networks.mp4 614.6 MB
  • 19. Object Detection with YOLO algorithm/03. YOLO paper.mp4 581.5 MB
  • 20. Image segmentation and Virtual Cloth Try-on with Stable Diffusion Inpainting/12. Building FiftyOne Data Augmentation Plugin with Stable Diffusion Inpainting.mp4 568.7 MB
  • 29. Sentiment Analysis with Transformers/03. Sentiment analysis with LSH Attention.mp4 504.0 MB
  • 11. MLOps with Weights and Biases/01. Experiment tracking.mp4 476.7 MB
  • 08. Data augmentation/01. Data augmentation with TensorFlow using tf.image and Keras Layers.mp4 476.5 MB
  • 28. Neural Machine Translation with Transformers/03. Building, training and testing Transformers.mp4 465.7 MB
  • 17. Transformers in Vision/01. Understanding VITs.mp4 422.2 MB
  • 22. Image generation/09. Face generation with GANs.mp4 410.9 MB
  • 19. Object Detection with YOLO algorithm/04. Dataset Preparation.mp4 401.1 MB
  • 35. Ecommerce search engine with Sentence transformers/04. Building,training and testing model.mp4 397.0 MB
  • 17. Transformers in Vision/02. Building VITs from scratch.mp4 396.2 MB
  • 02. Tensors and Variables/06. Linear Algebra Operations in Tensorflow.mp4 377.8 MB
  • 12. Human Emotions Detection/03. Modeling and training.mp4 367.4 MB
  • 13. Modern Convolutional Neural Networks/03. Resnet.mp4 358.8 MB
  • 04. Building Convolutional Neural Networks Malaria Diagnosis/06. How and Why Convolutional Neural Networks work.mp4 346.2 MB
  • 08. Data augmentation/03. Cutmix Data augmentation with TensorFlow 2 and intergration in tf.data.mp4 344.1 MB
  • 35. Ecommerce search engine with Sentence transformers/03. Dataset preparation.mp4 333.0 MB
  • 31. Sentiment Analysis with Deberta in Huggingface transformers/02. Data Preparation.mp4 332.8 MB
  • 11. MLOps with Weights and Biases/03. Dataset Versioning with Weights and Biases and TensorFlow 2.mp4 328.3 MB
  • 39. Automatic Speech Recognition/02. Understanding Speech recognition and Data Processing.mp4 312.1 MB
  • 19. Object Detection with YOLO algorithm/08. Testing.mp4 311.1 MB
  • 35. Ecommerce search engine with Sentence transformers/02. Problem Understanding and Sentence Embeddings.mp4 310.4 MB
  • 02. Tensors and Variables/03. Tensor Initialization and Casting.mp4 300.4 MB
  • 10. Tensorboard integration/01. Data logging.mp4 292.2 MB
  • 12. Human Emotions Detection/05. Tensorflow records.mp4 291.2 MB
  • 21. People counting/06. Data augmentation.mp4 264.7 MB
  • 21. People counting/03. Dataset preparation.mp4 261.5 MB
  • 20. Image segmentation and Virtual Cloth Try-on with Stable Diffusion Inpainting/10. Model Evaluation with FiftyOne.mp4 260.0 MB
  • 22. Image generation/06. How GANs work.mp4 239.3 MB
  • 09. Advanced Tensorflow Concepts/03. Custom training loops.mp4 238.4 MB
  • 38. Elon Musk Bot with BlenderBot in Huggingface transformers/02. Problem Understanding and Data Preparation.mp4 237.4 MB
  • 15. Understanding the blackbox/02. Grad-cam method.mp4 231.4 MB
  • 03. Building a Simple Neural Network in Tensorflow/04. Data Preparation.mp4 226.3 MB
  • 12. Human Emotions Detection/02. Data preparation.mp4 224.0 MB
  • 19. Object Detection with YOLO algorithm/07. Data augmentation.mp4 220.7 MB
  • 20. Image segmentation and Virtual Cloth Try-on with Stable Diffusion Inpainting/11. Virtual Cloth Try-on with Stable Diffusion Inpainting.mp4 219.6 MB
  • 07. Improving Model Performance/01. Tensorflow Callbacks.mp4 218.0 MB
  • 24. Sentiment Analysis with Recurrent neural networks/06. 1D Convolutional Neural Network.mp4 217.8 MB
  • 31. Sentiment Analysis with Deberta in Huggingface transformers/03. Building,training and testing model.mp4 216.7 MB
  • 02. Tensors and Variables/05. Maths Operations in Tensorflow.mp4 214.5 MB
  • 02. Tensors and Variables/07. Common Methods.mp4 212.7 MB
  • 24. Sentiment Analysis with Recurrent neural networks/05. Advanced RNNs (LSTM and GRU).mp4 212.1 MB
  • 25. Sentiment Analysis with transfer learning/01. Understanding Word2vec.mp4 209.3 MB
  • 13. Modern Convolutional Neural Networks/05. Mobilenet.mp4 207.5 MB
  • 18. Model deployment/01. Model Conversion from Tensorflow to Onnx.mp4 205.3 MB
  • 08. Data augmentation/04. Albumentations with TensorFlow 2 and PyTorch for Data augmentation.mp4 201.4 MB
  • 07. Improving Model Performance/04. Mitigating overfitting and underfitting.mp4 198.1 MB
  • 06. Evaluating Classification Models/01. Precision,Recall and Accuracy.mp4 195.8 MB
  • 13. Modern Convolutional Neural Networks/06. Efficientnet.mp4 194.3 MB
  • 36. Lyrics Generator with GPT2 in Huggingface transformers/03. Building,training and testing model.mp4 191.9 MB
  • 17. Transformers in Vision/03. Finetuning Huggingface transformers.mp4 190.1 MB
  • 13. Modern Convolutional Neural Networks/01. Alexnet.mp4 189.8 MB
  • 20. Image segmentation and Virtual Cloth Try-on with Stable Diffusion Inpainting/07. Data Visualization with FiftyOne.mp4 186.9 MB
  • 33. Named Entity Relation with Roberta in Huggingface transformers/02. Problem Understanding and Data Preparation.mp4 184.9 MB
  • 40. Essential Python Programming/14. Numpy Package.mp4 182.4 MB
  • 20. Image segmentation and Virtual Cloth Try-on with Stable Diffusion Inpainting/09. Model Creation.mp4 180.7 MB
  • 13. Modern Convolutional Neural Networks/04. Coding Resnets.mp4 180.5 MB
  • 03. Building a Simple Neural Network in Tensorflow/09. Validation and testing.mp4 178.5 MB
  • 27. Neural Machine Translation with Attention/03. Building, training and testing Bahdanau Attention.mp4 178.3 MB
  • 09. Advanced Tensorflow Concepts/01. Custom Loss and Metrics.mp4 177.7 MB
  • 39. Automatic Speech Recognition/03. Buillding and Training speech recognition model.mp4 177.6 MB
  • 10. Tensorboard integration/03. Hyperparameter tuning.mp4 175.1 MB
  • 36. Lyrics Generator with GPT2 in Huggingface transformers/02. Problem Understanding and Data Preparation.mp4 171.9 MB
  • 24. Sentiment Analysis with Recurrent neural networks/03. Data preparation.mp4 166.3 MB
  • 22. Image generation/07. The GAN loss.mp4 165.7 MB
  • 24. Sentiment Analysis with Recurrent neural networks/04. Building and training RNNs.mp4 164.6 MB
  • 20. Image segmentation and Virtual Cloth Try-on with Stable Diffusion Inpainting/05. Data Processing.mp4 163.6 MB
  • 08. Data augmentation/02. Mixup Data augmentation with TensorFlow 2 with intergration in tf.data.mp4 162.8 MB
  • 14. Transfer Learning/01. Leveraging pretrained models.mp4 160.8 MB
  • 18. Model deployment/02. Understanding quantization.mp4 158.1 MB
  • 15. Understanding the blackbox/01. Visualizing intermediate layers.mp4 157.3 MB
  • 18. Model deployment/05. Conversion to Tensorflow Lite.mp4 154.4 MB
  • 22. Image generation/04. VAE training and digit generation.mp4 153.2 MB
  • 26. Neural Machine Translation with Recurrent Neural Networks/03. Data preparation.mp4 152.8 MB
  • 18. Model deployment/04. Quantization aware training.mp4 147.2 MB
  • 04. Building Convolutional Neural Networks Malaria Diagnosis/03. Data Preparation.mp4 145.4 MB
  • 12. Human Emotions Detection/04. Data augmentation.mp4 142.4 MB
  • 11. MLOps with Weights and Biases/02. Hyperparameter tuning with wandb.mp4 141.7 MB
  • 30. Transfer Learning and Generalized Language Models/06. Gpt2.mp4 140.4 MB
  • 05. Building more advanced Models with Functional API, Subclassing and Custom Layers/01. Functional API.mp4 138.7 MB
  • 28. Neural Machine Translation with Transformers/04. Building Transformers with Custom Attention Layer.mp4 135.3 MB
  • 17. Transformers in Vision/06. Swin transformers.mp4 132.7 MB
  • 22. Image generation/08. Improving GAN training.mp4 130.8 MB
  • 17. Transformers in Vision/04. Model evaluation with wandb.mp4 129.4 MB
  • 23. Text Preprocessing for Sentiment analysis/02. Text standardization.mp4 123.3 MB
  • 05. Building more advanced Models with Functional API, Subclassing and Custom Layers/02. Model Subclassing.mp4 119.6 MB
  • 20. Image segmentation and Virtual Cloth Try-on with Stable Diffusion Inpainting/04. Data Splitting.mp4 119.0 MB
  • 40. Essential Python Programming/02. Variables and Basic Operators.mp4 118.8 MB
  • 13. Modern Convolutional Neural Networks/02. Vggnet.mp4 118.2 MB
  • 25. Sentiment Analysis with transfer learning/04. Visualizing embeddings.mp4 113.1 MB
  • 22. Image generation/05. Latent space visualizations.mp4 112.2 MB
  • 34. Extractive Question Answering with Longformer in Huggingface transformers/03. Building,training and testing model.mp4 110.9 MB
  • 07. Improving Model Performance/02. Learning rate scheduling.mp4 109.9 MB
  • 22. Image generation/03. Understanding variational autoencoders.mp4 108.6 MB
  • 30. Transfer Learning and Generalized Language Models/04. Bert.mp4 107.5 MB
  • 20. Image segmentation and Virtual Cloth Try-on with Stable Diffusion Inpainting/08. Understanding Segformer.mp4 107.1 MB
  • 18. Model deployment/09. Load tesing the Emotions Detection API with Locust.mp4 106.2 MB
  • 11. MLOps with Weights and Biases/04. Model Versioning with Weights and Biases and TensorFlow 2.mp4 104.7 MB
  • 18. Model deployment/08. Deploy the Emotions Detection API to the Cloud.mp4 104.2 MB
  • 14. Transfer Learning/02. Finetuning.mp4 103.8 MB
  • 04. Building Convolutional Neural Networks Malaria Diagnosis/11. Loading and Saving Tensorflow Models to Google Drive.mp4 102.2 MB
  • 38. Elon Musk Bot with BlenderBot in Huggingface transformers/03. Building,training and testing model.mp4 101.6 MB
  • 26. Neural Machine Translation with Recurrent Neural Networks/02. Understanding Machine Translation.mp4 101.3 MB
  • 03. Building a Simple Neural Network in Tensorflow/05. Linear Regression Model.mp4 100.4 MB
  • 03. Building a Simple Neural Network in Tensorflow/06. Error sanctioning.mp4 100.0 MB
  • 16. Ensembling and class imbalance/02. Class Imbalance.mp4 99.2 MB
  • 02. Tensors and Variables/04. Indexing.mp4 97.2 MB
  • 33. Named Entity Relation with Roberta in Huggingface transformers/03. Building,training and testing model.mp4 97.1 MB
  • 30. Transfer Learning and Generalized Language Models/03. Gpt.mp4 94.5 MB
  • 27. Neural Machine Translation with Attention/02. Understanding Bahdanau Attention.mp4 91.4 MB
  • 23. Text Preprocessing for Sentiment analysis/01. Understanding sentiment analysis.mp4 90.3 MB
  • 26. Neural Machine Translation with Recurrent Neural Networks/06. Coding BLEU score from scratch.mp4 90.2 MB
  • 02. Tensors and Variables/08. Ragged Tensors.mp4 88.3 MB
  • 26. Neural Machine Translation with Recurrent Neural Networks/04. Building, training and testing Model.mp4 87.8 MB
  • 25. Sentiment Analysis with transfer learning/02. Integrating pretrained Word2vec embeddings.mp4 85.6 MB
  • 32. Intent Classification with Deberta in Huggingface transformers/03. Building,training and testing model.mp4 83.7 MB
  • 21. People counting/02. People Counting - Shangai Tech Dataset.mp4 82.7 MB
  • 40. Essential Python Programming/12. Decorators.mp4 82.6 MB
  • 18. Model deployment/06. What is an API.mp4 82.5 MB
  • 40. Essential Python Programming/03. Conditional Statements.mp4 79.8 MB
  • 40. Essential Python Programming/05. Methods.mp4 79.0 MB
  • 03. Building a Simple Neural Network in Tensorflow/10. Corrective Measures.mp4 72.0 MB
  • 03. Building a Simple Neural Network in Tensorflow/11. TensorFlow Datasets.mp4 71.1 MB
  • 10. Tensorboard integration/04. Profiling and other visualizations with Tensorboard.mp4 70.1 MB
  • 20. Image segmentation and Virtual Cloth Try-on with Stable Diffusion Inpainting/06. Data Visualization with Matplotlib.mp4 68.4 MB
  • 17. Transformers in Vision/05. Data efficient transformers.mp4 66.5 MB
  • 37. Grammatical Error Correction with T5 in Huggingface transformers/02. Problem Understanding and Data Preparation.mp4 64.8 MB
  • 18. Model deployment/03. Practical quantization of Onnx.mp4 64.4 MB
  • 40. Essential Python Programming/04. Loops.mp4 63.9 MB
  • 07. Improving Model Performance/03. Model checkpointing.mp4 61.5 MB
  • 04. Building Convolutional Neural Networks Malaria Diagnosis/09. Convnet training.mp4 58.7 MB
  • 23. Text Preprocessing for Sentiment analysis/04. One-hot encoding and Bag of Words.mp4 57.8 MB
  • 30. Transfer Learning and Generalized Language Models/08. T5.mp4 57.1 MB
  • 24. Sentiment Analysis with Recurrent neural networks/02. How Recurrent neural networks work.mp4 56.3 MB
  • 37. Grammatical Error Correction with T5 in Huggingface transformers/03. Building,training and testing model.mp4 55.3 MB
  • 04. Building Convolutional Neural Networks Malaria Diagnosis/02. Task understanding.mp4 54.8 MB
  • 32. Intent Classification with Deberta in Huggingface transformers/02. Problem Understanding and Data Preparation.mp4 51.7 MB
  • 23. Text Preprocessing for Sentiment analysis/03. Tokenization.mp4 50.8 MB
  • 03. Building a Simple Neural Network in Tensorflow/07. Training and Optimization.mp4 50.6 MB
  • 29. Sentiment Analysis with Transformers/02. Sentiment analysis with Transformer encoder.mp4 50.5 MB
  • 28. Neural Machine Translation with Transformers/05. Visualizing Attention scores.mp4 50.0 MB
  • 05. Building more advanced Models with Functional API, Subclassing and Custom Layers/03. Custom Layers.mp4 49.3 MB
  • 40. Essential Python Programming/07. Operator Overloading.mp4 48.3 MB
  • 21. People counting/05. Training and optimization.mp4 46.6 MB
  • 09. Advanced Tensorflow Concepts/02. Eager and graph modes.mp4 44.9 MB
  • 04. Building Convolutional Neural Networks Malaria Diagnosis/07. Building Convnets in Tensorflow.mp4 44.2 MB
  • 25. Sentiment Analysis with transfer learning/03. Testing.mp4 44.2 MB
  • 01. Introduction/02. General Introduction.mp4 41.5 MB
  • 23. Text Preprocessing for Sentiment analysis/05. Term frequency - Inverse Document frequency (TF-IDF).mp4 40.2 MB
  • 30. Transfer Learning and Generalized Language Models/01. Understanding Transfer Learning.mp4 39.0 MB
  • 40. Essential Python Programming/06. Objects and Classes.mp4 38.7 MB
  • 06. Evaluating Classification Models/02. Confusion Matrix.mp4 37.0 MB
  • 16. Ensembling and class imbalance/01. Ensembling.mp4 35.5 MB
  • 26. Neural Machine Translation with Recurrent Neural Networks/05. Understanding BLEU Score.mp4 35.1 MB
  • 23. Text Preprocessing for Sentiment analysis/06. Embeddings.mp4 34.5 MB
  • 40. Essential Python Programming/13. Generators.mp4 31.7 MB
  • 40. Essential Python Programming/09. Inheritance.mp4 31.0 MB
  • 06. Evaluating Classification Models/03. ROC Plots.mp4 30.3 MB
  • 21. People counting/04. CSRNET.mp4 29.9 MB
  • 40. Essential Python Programming/08. Method Types.mp4 28.2 MB
  • 19. Object Detection with YOLO algorithm/05. YOLO Resnet.mp4 27.7 MB
  • 03. Building a Simple Neural Network in Tensorflow/08. Performance Measurement.mp4 27.6 MB
  • 02. Tensors and Variables/02. Tensor Basics.mp4 26.7 MB
  • 20. Image segmentation and Virtual Cloth Try-on with Stable Diffusion Inpainting/03. Data Downloading.mp4 26.3 MB
  • 04. Building Convolutional Neural Networks Malaria Diagnosis/08. Binary Crossentropy loss.mp4 26.1 MB
  • 30. Transfer Learning and Generalized Language Models/05. Albert.mp4 25.6 MB
  • 04. Building Convolutional Neural Networks Malaria Diagnosis/05. Data Processing.mp4 24.4 MB
  • 20. Image segmentation and Virtual Cloth Try-on with Stable Diffusion Inpainting/02. Problem Understanding.mp4 24.0 MB
  • 19. Object Detection with YOLO algorithm/09. Data generators.mp4 22.3 MB
  • 02. Tensors and Variables/10. String Tensors.mp4 22.2 MB
  • 22. Image generation/02. Introduction to image generation.mp4 20.5 MB
  • 19. Object Detection with YOLO algorithm/02. Understanding object detection.mp4 19.6 MB
  • 02. Tensors and Variables/11. Tensorflow Variables.mp4 19.5 MB
  • 04. Building Convolutional Neural Networks Malaria Diagnosis/10. Model evaluation and testing.mp4 18.0 MB
  • 30. Transfer Learning and Generalized Language Models/02. Ulmfit.mp4 17.9 MB
  • 40. Essential Python Programming/01. Python Installation.mp4 14.6 MB
  • 01. Introduction/01. Welcome.mp4 14.5 MB
  • 30. Transfer Learning and Generalized Language Models/07. Roberta.mp4 14.5 MB
  • 40. Essential Python Programming/15. Matplotlib Introduction.mp4 14.2 MB
  • 03. Building a Simple Neural Network in Tensorflow/03. Task Understanding.mp4 13.8 MB
  • 10. Tensorboard integration/02. Viewing model graphs.mp4 10.0 MB
  • 04. Building Convolutional Neural Networks Malaria Diagnosis/04. Data visualization.mp4 10.0 MB
  • 02. Tensors and Variables/09. Sparse Tensors.mp4 9.6 MB
  • 40. Essential Python Programming/11. Polymorphism.mp4 6.8 MB
  • 40. Essential Python Programming/10. Encapsulation.mp4 6.7 MB
  • 18. Model deployment/07. Building the Emotions Detection API with Fastapi.vtt 101.0 kB
  • 19. Object Detection with YOLO algorithm/06. YOLO Loss.vtt 82.1 kB
  • 19. Object Detection with YOLO algorithm/03. YOLO paper.vtt 81.7 kB
  • 28. Neural Machine Translation with Transformers/02. Understanding Transformer Networks.vtt 78.6 kB
  • 34. Extractive Question Answering with Longformer in Huggingface transformers/02. Problem Understanding and Data Preparation.vtt 76.5 kB
  • 11. MLOps with Weights and Biases/01. Experiment tracking.vtt 72.5 kB
  • 12. Human Emotions Detection/03. Modeling and training.vtt 69.6 kB
  • 02. Tensors and Variables/06. Linear Algebra Operations in Tensorflow.vtt 69.0 kB
  • 17. Transformers in Vision/02. Building VITs from scratch.vtt 68.6 kB
  • 20. Image segmentation and Virtual Cloth Try-on with Stable Diffusion Inpainting/12. Building FiftyOne Data Augmentation Plugin with Stable Diffusion Inpainting.vtt 65.5 kB
  • 28. Neural Machine Translation with Transformers/03. Building, training and testing Transformers.vtt 63.6 kB
  • 22. Image generation/09. Face generation with GANs.vtt 60.4 kB
  • 31. Sentiment Analysis with Deberta in Huggingface transformers/02. Data Preparation.vtt 59.3 kB
  • 04. Building Convolutional Neural Networks Malaria Diagnosis/06. How and Why Convolutional Neural Networks work.vtt 59.3 kB
  • 40. Essential Python Programming/14. Numpy Package.vtt 58.0 kB
  • 35. Ecommerce search engine with Sentence transformers/04. Building,training and testing model.vtt 57.8 kB
  • 19. Object Detection with YOLO algorithm/04. Dataset Preparation.vtt 53.4 kB
  • 21. People counting/03. Dataset preparation.vtt 50.9 kB
  • 35. Ecommerce search engine with Sentence transformers/03. Dataset preparation.vtt 46.3 kB
  • 35. Ecommerce search engine with Sentence transformers/02. Problem Understanding and Sentence Embeddings.vtt 46.0 kB
  • 12. Human Emotions Detection/05. Tensorflow records.vtt 45.8 kB
  • 24. Sentiment Analysis with Recurrent neural networks/05. Advanced RNNs (LSTM and GRU).vtt 44.2 kB
  • 10. Tensorboard integration/01. Data logging.vtt 42.3 kB
  • 02. Tensors and Variables/05. Maths Operations in Tensorflow.vtt 41.9 kB
  • 13. Modern Convolutional Neural Networks/03. Resnet.vtt 41.5 kB
  • 19. Object Detection with YOLO algorithm/08. Testing.vtt 40.3 kB
  • 39. Automatic Speech Recognition/02. Understanding Speech recognition and Data Processing.vtt 39.2 kB
  • 24. Sentiment Analysis with Recurrent neural networks/06. 1D Convolutional Neural Network.vtt 38.3 kB
  • 02. Tensors and Variables/07. Common Methods.vtt 37.5 kB
  • 12. Human Emotions Detection/02. Data preparation.vtt 36.7 kB
  • 26. Neural Machine Translation with Recurrent Neural Networks/03. Data preparation.vtt 36.3 kB
  • 26. Neural Machine Translation with Recurrent Neural Networks/04. Building, training and testing Model.vtt 36.2 kB
  • 20. Image segmentation and Virtual Cloth Try-on with Stable Diffusion Inpainting/10. Model Evaluation with FiftyOne.vtt 36.2 kB
  • 01. Introduction/02. General Introduction.vtt 35.8 kB
  • 31. Sentiment Analysis with Deberta in Huggingface transformers/03. Building,training and testing model.vtt 35.7 kB
  • 07. Improving Model Performance/04. Mitigating overfitting and underfitting.vtt 35.7 kB
  • 24. Sentiment Analysis with Recurrent neural networks/03. Data preparation.vtt 34.9 kB
  • 33. Named Entity Relation with Roberta in Huggingface transformers/02. Problem Understanding and Data Preparation.vtt 34.1 kB
  • 36. Lyrics Generator with GPT2 in Huggingface transformers/03. Building,training and testing model.vtt 33.6 kB
  • 20. Image segmentation and Virtual Cloth Try-on with Stable Diffusion Inpainting/09. Model Creation.vtt 33.4 kB
  • 09. Advanced Tensorflow Concepts/03. Custom training loops.vtt 33.4 kB
  • 21. People counting/06. Data augmentation.vtt 33.2 kB
  • 20. Image segmentation and Virtual Cloth Try-on with Stable Diffusion Inpainting/08. Understanding Segformer.vtt 32.9 kB
  • 38. Elon Musk Bot with BlenderBot in Huggingface transformers/02. Problem Understanding and Data Preparation.vtt 32.8 kB
  • 20. Image segmentation and Virtual Cloth Try-on with Stable Diffusion Inpainting/11. Virtual Cloth Try-on with Stable Diffusion Inpainting.vtt 32.5 kB
  • 07. Improving Model Performance/01. Tensorflow Callbacks.vtt 32.1 kB
  • 25. Sentiment Analysis with transfer learning/01. Understanding Word2vec.vtt 32.0 kB
  • 02. Tensors and Variables/04. Indexing.vtt 31.9 kB
  • 40. Essential Python Programming/02. Variables and Basic Operators.vtt 31.4 kB
  • 22. Image generation/08. Improving GAN training.vtt 31.0 kB
  • 03. Building a Simple Neural Network in Tensorflow/04. Data Preparation.vtt 31.0 kB
  • 06. Evaluating Classification Models/01. Precision,Recall and Accuracy.vtt 30.6 kB
  • 19. Object Detection with YOLO algorithm/07. Data augmentation.vtt 30.2 kB
  • 24. Sentiment Analysis with Recurrent neural networks/04. Building and training RNNs.vtt 29.9 kB
  • 11. MLOps with Weights and Biases/02. Hyperparameter tuning with wandb.vtt 29.5 kB
  • 13. Modern Convolutional Neural Networks/05. Mobilenet.vtt 29.5 kB
  • 18. Model deployment/01. Model Conversion from Tensorflow to Onnx.vtt 29.4 kB
  • 17. Transformers in Vision/03. Finetuning Huggingface transformers.vtt 29.3 kB
  • 13. Modern Convolutional Neural Networks/04. Coding Resnets.vtt 28.9 kB
  • 39. Automatic Speech Recognition/03. Buillding and Training speech recognition model.vtt 28.7 kB
  • 03. Building a Simple Neural Network in Tensorflow/09. Validation and testing.vtt 28.7 kB
  • 14. Transfer Learning/01. Leveraging pretrained models.vtt 28.4 kB
  • 36. Lyrics Generator with GPT2 in Huggingface transformers/02. Problem Understanding and Data Preparation.vtt 28.1 kB
  • 17. Transformers in Vision/04. Model evaluation with wandb.vtt 28.0 kB
  • 15. Understanding the blackbox/02. Grad-cam method.vtt 27.9 kB
  • 20. Image segmentation and Virtual Cloth Try-on with Stable Diffusion Inpainting/05. Data Processing.vtt 27.8 kB
  • 04. Building Convolutional Neural Networks Malaria Diagnosis/03. Data Preparation.vtt 27.7 kB
  • 27. Neural Machine Translation with Attention/03. Building, training and testing Bahdanau Attention.vtt 27.4 kB
  • 08. Data augmentation/04. Albumentations with TensorFlow 2 and PyTorch for Data augmentation.vtt 27.2 kB
  • 09. Advanced Tensorflow Concepts/01. Custom Loss and Metrics.vtt 26.4 kB
  • 20. Image segmentation and Virtual Cloth Try-on with Stable Diffusion Inpainting/07. Data Visualization with FiftyOne.vtt 26.0 kB
  • 10. Tensorboard integration/03. Hyperparameter tuning.vtt 25.8 kB
  • 28. Neural Machine Translation with Transformers/04. Building Transformers with Custom Attention Layer.vtt 25.4 kB
  • 24. Sentiment Analysis with Recurrent neural networks/02. How Recurrent neural networks work.vtt 25.3 kB
  • 22. Image generation/06. How GANs work.vtt 25.3 kB
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  • 12. Human Emotions Detection/01. Link to Code.html 235 Bytes
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  • 39. Automatic Speech Recognition/01. Link to Code.html 213 Bytes
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  • 20. Image segmentation and Virtual Cloth Try-on with Stable Diffusion Inpainting/01. Link to Code.html 154 Bytes
  • 03. Building a Simple Neural Network in Tensorflow/01. Link to Dataset.html 147 Bytes

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