Udemy - PyTorch for Deep Learning with Python Bootcamp (9.2019)

Creation Time	July 17, 2025, 10:42 p.m.
Last Access Time	July 17, 2025, 10:42 p.m.
File Size	6.7 GB
Keywords	for Python - Deep Udemy PyTorch 2019 Learning 9 Bootcamp with
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Total Files	209
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1. Course Overview, Installs, and Setup/1.1 PYTORCH_NOTEBOOKS.zip.zip 196.0 MB
1. Course Overview, Installs, and Setup/2.1 PYTORCH_NOTEBOOKS.zip.zip 196.0 MB
8. CNN - Convolutional Neural Networks/17. Loading Real Image Data - Part Two.mp4 164.2 MB
7. ANN - Artificial Neural Networks/16. Full ANN Code Along - Regression - Part One - Feature Engineering.mp4 161.6 MB
8. CNN - Convolutional Neural Networks/18. CNN on Custom Images - Part One - Loading Data.mp4 158.9 MB
7. ANN - Artificial Neural Networks/10. Linear Regression with PyTorch - Part Two.mp4 149.8 MB
8. CNN - Convolutional Neural Networks/15. CIFAR-10 DataSet with CNN - Code Along - Part Two.mp4 146.3 MB
9. Recurrent Neural Networks/10. RNN on a Time Series - Part Two.mp4 140.7 MB
9. Recurrent Neural Networks/8. Basic RNN - Training and Forecasting.mp4 136.7 MB
7. ANN - Artificial Neural Networks/22. ANN - Exercise Solutions.mp4 135.8 MB
7. ANN - Artificial Neural Networks/17. Full ANN Code Along - Regression - Part 2 - Categorical and Continuous Features.mp4 129.2 MB
8. CNN - Convolutional Neural Networks/11. MNIST with CNN - Code Along - Part One.mp4 122.9 MB
7. ANN - Artificial Neural Networks/19. Full ANN Code Along - Regression - Part Four - Training and Evaluation.mp4 117.2 MB
8. CNN - Convolutional Neural Networks/3. ANN with MNIST - Part One - Data.mp4 116.7 MB
1. Course Overview, Installs, and Setup/2. Installation and Environment Setup.mp4 116.0 MB
7. ANN - Artificial Neural Networks/18. Full ANN Code Along - Regression - Part Three - Tabular Model.mp4 115.1 MB
10. Using a GPU with PyTorch and CUDA/2. Using GPU for PyTorch.mp4 114.1 MB
11. NLP with PyTorch/2. Encoding Text Data.mp4 109.4 MB
7. ANN - Artificial Neural Networks/11. DataSets with PyTorch.mp4 109.1 MB
8. CNN - Convolutional Neural Networks/12. MNIST with CNN - Code Along - Part Two.mp4 105.5 MB
10. Using a GPU with PyTorch and CUDA/1. Why do we need GPUs.mp4 102.4 MB
8. CNN - Convolutional Neural Networks/20. CNN on Custom Images - Part Three - PreTrained Networks.mp4 100.7 MB
11. NLP with PyTorch/3. Generating Training Batches.mp4 96.5 MB
6. Machine Learning Concepts Overview/4. Evaluating Performance - Classification Error Metrics.mp4 93.8 MB
7. ANN - Artificial Neural Networks/13. Basic PyTorch ANN - Part Two.mp4 93.2 MB
8. CNN - Convolutional Neural Networks/5. ANN with MNIST - Part Three - Training.mp4 92.0 MB
9. Recurrent Neural Networks/6. RNN - Creating Batches with Data.mp4 91.2 MB
8. CNN - Convolutional Neural Networks/16. Loading Real Image Data - Part One.mp4 91.1 MB
9. Recurrent Neural Networks/7. Basic RNN - Creating the LSTM Model.mp4 89.8 MB
7. ANN - Artificial Neural Networks/6. Theory - Cost Functions and Gradient Descent.mp4 89.5 MB
9. Recurrent Neural Networks/9. RNN on a Time Series - Part One.mp4 89.0 MB
7. ANN - Artificial Neural Networks/14. Basic PyTorch ANN - Part Three.mp4 88.6 MB
4. Crash Course Pandas/3. Pandas DataFrames - Part One.mp4 87.8 MB
9. Recurrent Neural Networks/12. RNN Exercise - Solutions.mp4 87.1 MB
8. CNN - Convolutional Neural Networks/7. Image Filters and Kernels.mp4 87.0 MB
5. PyTorch Basics/3. Tensor Basics - Part Two.mp4 82.5 MB
11. NLP with PyTorch/5. Training the LSTM Model.mp4 81.7 MB
8. CNN - Convolutional Neural Networks/19. CNN on Custom Images - Part Two - Training and Evaluating Model.mp4 76.2 MB
11. NLP with PyTorch/4. Creating the LSTM Model.mp4 73.6 MB
4. Crash Course Pandas/4. Pandas DataFrames - Part Two.mp4 73.1 MB
11. NLP with PyTorch/7. Generating Predictions.mp4 72.6 MB
5. PyTorch Basics/4. Tensor Operations.mp4 71.3 MB
7. ANN - Artificial Neural Networks/4. Theory - Activation Functions.mp4 71.1 MB
7. ANN - Artificial Neural Networks/8. PyTorch Gradients.mp4 70.3 MB
7. ANN - Artificial Neural Networks/20. Full ANN Code Along - Classification Example.mp4 68.7 MB
8. CNN - Convolutional Neural Networks/8. Convolutional Layers.mp4 68.6 MB
4. Crash Course Pandas/7. Data Input and Output.mp4 68.3 MB
7. ANN - Artificial Neural Networks/7. Theory - BackPropagation.mp4 67.9 MB
8. CNN - Convolutional Neural Networks/4. ANN with MNIST - Part Two - Creating the Network.mp4 64.3 MB
4. Crash Course Pandas/9. Pandas Exercises - Solutions.mp4 63.7 MB
8. CNN - Convolutional Neural Networks/22. CNN Exercise Solutions.mp4 61.3 MB
7. ANN - Artificial Neural Networks/12. Basic Pytorch ANN - Part One.mp4 60.8 MB
3. Crash Course NumPy/2. NumPy Arrays.mp4 60.4 MB
3. Crash Course NumPy/4. Numpy Index Selection.mp4 58.9 MB
8. CNN - Convolutional Neural Networks/6. ANN with MNIST - Part Four - Evaluation.mp4 58.4 MB
7. ANN - Artificial Neural Networks/21. ANN - Exercise Overview.mp4 57.6 MB
8. CNN - Convolutional Neural Networks/14. CIFAR-10 DataSet with CNN - Code Along - Part One.mp4 56.7 MB
7. ANN - Artificial Neural Networks/2. Theory - Perceptron Model.mp4 55.8 MB
3. Crash Course NumPy/3. NumPy Arrays Part Two.mp4 54.9 MB
3. Crash Course NumPy/7. Numpy Exercises - Solutions.mp4 54.8 MB
8. CNN - Convolutional Neural Networks/13. MNIST with CNN - Code Along - Part Three.mp4 54.8 MB
7. ANN - Artificial Neural Networks/5. Multi-Class Classification.mp4 53.9 MB
7. ANN - Artificial Neural Networks/9. Linear Regression with PyTorch.mp4 51.5 MB
9. Recurrent Neural Networks/4. LSTMS and GRU.mp4 49.0 MB
6. Machine Learning Concepts Overview/2. Supervised Learning.mp4 45.4 MB
4. Crash Course Pandas/2. Pandas Series.mp4 45.1 MB
4. Crash Course Pandas/6. Pandas Operations.mp4 43.8 MB
5. PyTorch Basics/2. Tensor Basics.mp4 42.5 MB
7. ANN - Artificial Neural Networks/3. Theory - Neural Network.mp4 41.4 MB
3. Crash Course NumPy/5. NumPy Operations.mp4 40.4 MB
9. Recurrent Neural Networks/11. RNN Exercise.mp4 38.9 MB
1. Course Overview, Installs, and Setup/1. COURSE OVERVIEW LECTURE - PLEASE DO NOT SKIP!.mp4 38.8 MB
9. Recurrent Neural Networks/5. RNN Batches Theory.mp4 37.8 MB
7. ANN - Artificial Neural Networks/15. Introduction to Full ANN with PyTorch.mp4 35.2 MB
5. PyTorch Basics/7. PyTorch Basics - Exercise Solutions.mp4 35.0 MB
9. Recurrent Neural Networks/2. RNN Basic Theory.mp4 35.0 MB
5. PyTorch Basics/5. Tensor Operations - Part Two.mp4 34.0 MB
8. CNN - Convolutional Neural Networks/9. Pooling Layers.mp4 33.0 MB
9. Recurrent Neural Networks/3. Vanishing Gradients.mp4 32.5 MB
4. Crash Course Pandas/8. Pandas Exercises.mp4 31.0 MB
6. Machine Learning Concepts Overview/3. Overfitting.mp4 30.4 MB
4. Crash Course Pandas/5. GroupBy Operations.mp4 29.0 MB
6. Machine Learning Concepts Overview/5. Evaluating Performance - Regression Error Metrics.mp4 27.9 MB
8. CNN - Convolutional Neural Networks/21. CNN Exercise.mp4 27.6 MB
6. Machine Learning Concepts Overview/1. What is Machine Learning.mp4 22.4 MB
6. Machine Learning Concepts Overview/6. Unsupervised Learning.mp4 21.8 MB
5. PyTorch Basics/6. PyTorch Basics - Exercise.mp4 17.4 MB
8. CNN - Convolutional Neural Networks/2. Understanding the MNIST data set.mp4 16.8 MB
5. PyTorch Basics/1. PyTorch Basics Introduction.mp4 16.8 MB
11. NLP with PyTorch/1. Introduction to NLP with PyTorch.mp4 16.0 MB
3. Crash Course NumPy/6. Numpy Exercises.mp4 12.3 MB
8. CNN - Convolutional Neural Networks/10. MNIST Data Revisited.mp4 10.8 MB
8. CNN - Convolutional Neural Networks/1. Introduction to CNNs.mp4 9.7 MB
9. Recurrent Neural Networks/1. Introduction to Recurrent Neural Networks.mp4 9.5 MB
7. ANN - Artificial Neural Networks/1. Introduction to ANN Section.mp4 8.7 MB
4. Crash Course Pandas/1. Pandas Overview.mp4 6.4 MB
3. Crash Course NumPy/1. Introduction to NumPy.mp4 3.9 MB
8. CNN - Convolutional Neural Networks/18. CNN on Custom Images - Part One - Loading Data.vtt 28.2 KB
1. Course Overview, Installs, and Setup/2. Installation and Environment Setup.vtt 25.9 KB
8. CNN - Convolutional Neural Networks/3. ANN with MNIST - Part One - Data.vtt 25.8 KB
7. ANN - Artificial Neural Networks/10. Linear Regression with PyTorch - Part Two.vtt 25.2 KB
9. Recurrent Neural Networks/8. Basic RNN - Training and Forecasting.vtt 25.1 KB
7. ANN - Artificial Neural Networks/16. Full ANN Code Along - Regression - Part One - Feature Engineering.vtt 24.6 KB
8. CNN - Convolutional Neural Networks/15. CIFAR-10 DataSet with CNN - Code Along - Part Two.vtt 24.2 KB
8. CNN - Convolutional Neural Networks/11. MNIST with CNN - Code Along - Part One.vtt 24.1 KB
7. ANN - Artificial Neural Networks/6. Theory - Cost Functions and Gradient Descent.vtt 23.9 KB
8. CNN - Convolutional Neural Networks/17. Loading Real Image Data - Part Two.vtt 23.8 KB
9. Recurrent Neural Networks/10. RNN on a Time Series - Part Two.vtt 23.5 KB
7. ANN - Artificial Neural Networks/17. Full ANN Code Along - Regression - Part 2 - Categorical and Continuous Features.vtt 23.0 KB
10. Using a GPU with PyTorch and CUDA/2. Using GPU for PyTorch.vtt 21.9 KB
6. Machine Learning Concepts Overview/4. Evaluating Performance - Classification Error Metrics.vtt 21.9 KB
8. CNN - Convolutional Neural Networks/12. MNIST with CNN - Code Along - Part Two.vtt 21.4 KB
8. CNN - Convolutional Neural Networks/16. Loading Real Image Data - Part One.vtt 21.2 KB
7. ANN - Artificial Neural Networks/11. DataSets with PyTorch.vtt 20.2 KB
7. ANN - Artificial Neural Networks/22. ANN - Exercise Solutions.vtt 19.5 KB
7. ANN - Artificial Neural Networks/18. Full ANN Code Along - Regression - Part Three - Tabular Model.vtt 19.3 KB
7. ANN - Artificial Neural Networks/13. Basic PyTorch ANN - Part Two.vtt 19.3 KB
7. ANN - Artificial Neural Networks/19. Full ANN Code Along - Regression - Part Four - Training and Evaluation.vtt 19.1 KB
11. NLP with PyTorch/2. Encoding Text Data.vtt 18.8 KB
8. CNN - Convolutional Neural Networks/20. CNN on Custom Images - Part Three - PreTrained Networks.vtt 18.7 KB
8. CNN - Convolutional Neural Networks/5. ANN with MNIST - Part Three - Training.vtt 18.6 KB
9. Recurrent Neural Networks/9. RNN on a Time Series - Part One.vtt 18.6 KB
5. PyTorch Basics/3. Tensor Basics - Part Two.vtt 18.5 KB
8. CNN - Convolutional Neural Networks/8. Convolutional Layers.vtt 18.3 KB
7. ANN - Artificial Neural Networks/7. Theory - BackPropagation.vtt 18.0 KB
10. Using a GPU with PyTorch and CUDA/1. Why do we need GPUs.vtt 17.4 KB
5. PyTorch Basics/4. Tensor Operations.vtt 17.2 KB
7. ANN - Artificial Neural Networks/14. Basic PyTorch ANN - Part Three.vtt 16.9 KB
8. CNN - Convolutional Neural Networks/19. CNN on Custom Images - Part Two - Training and Evaluating Model.vtt 16.7 KB
11. NLP with PyTorch/3. Generating Training Batches.vtt 16.5 KB
4. Crash Course Pandas/3. Pandas DataFrames - Part One.vtt 16.4 KB
9. Recurrent Neural Networks/7. Basic RNN - Creating the LSTM Model.vtt 16.0 KB
8. CNN - Convolutional Neural Networks/7. Image Filters and Kernels.vtt 15.8 KB
9. Recurrent Neural Networks/6. RNN - Creating Batches with Data.vtt 15.5 KB
7. ANN - Artificial Neural Networks/8. PyTorch Gradients.vtt 15.5 KB
9. Recurrent Neural Networks/4. LSTMS and GRU.vtt 14.7 KB
7. ANN - Artificial Neural Networks/12. Basic Pytorch ANN - Part One.vtt 14.5 KB
7. ANN - Artificial Neural Networks/4. Theory - Activation Functions.vtt 14.3 KB
3. Crash Course NumPy/4. Numpy Index Selection.vtt 14.2 KB
7. ANN - Artificial Neural Networks/5. Multi-Class Classification.vtt 14.1 KB
3. Crash Course NumPy/2. NumPy Arrays.vtt 13.6 KB
11. NLP with PyTorch/4. Creating the LSTM Model.vtt 13.5 KB
7. ANN - Artificial Neural Networks/9. Linear Regression with PyTorch.vtt 13.5 KB
4. Crash Course Pandas/4. Pandas DataFrames - Part Two.vtt 13.5 KB
9. Recurrent Neural Networks/12. RNN Exercise - Solutions.vtt 13.4 KB
4. Crash Course Pandas/7. Data Input and Output.vtt 13.2 KB
8. CNN - Convolutional Neural Networks/4. ANN with MNIST - Part Two - Creating the Network.vtt 13.1 KB
7. ANN - Artificial Neural Networks/2. Theory - Perceptron Model.vtt 13.0 KB
4. Crash Course Pandas/2. Pandas Series.vtt 12.7 KB
11. NLP with PyTorch/5. Training the LSTM Model.vtt 12.6 KB
4. Crash Course Pandas/6. Pandas Operations.vtt 11.7 KB
11. NLP with PyTorch/7. Generating Predictions.vtt 11.6 KB
8. CNN - Convolutional Neural Networks/13. MNIST with CNN - Code Along - Part Three.vtt 11.5 KB
8. CNN - Convolutional Neural Networks/6. ANN with MNIST - Part Four - Evaluation.vtt 11.1 KB
6. Machine Learning Concepts Overview/2. Supervised Learning.vtt 10.9 KB
9. Recurrent Neural Networks/5. RNN Batches Theory.vtt 10.6 KB
3. Crash Course NumPy/3. NumPy Arrays Part Two.vtt 10.4 KB
6. Machine Learning Concepts Overview/3. Overfitting.vtt 10.4 KB
4. Crash Course Pandas/9. Pandas Exercises - Solutions.vtt 10.3 KB
1. Course Overview, Installs, and Setup/1. COURSE OVERVIEW LECTURE - PLEASE DO NOT SKIP!.vtt 10.1 KB
9. Recurrent Neural Networks/3. Vanishing Gradients.vtt 9.6 KB
7. ANN - Artificial Neural Networks/3. Theory - Neural Network.vtt 9.6 KB
7. ANN - Artificial Neural Networks/20. Full ANN Code Along - Classification Example.vtt 9.5 KB
9. Recurrent Neural Networks/2. RNN Basic Theory.vtt 9.5 KB
5. PyTorch Basics/2. Tensor Basics.vtt 9.5 KB
7. ANN - Artificial Neural Networks/15. Introduction to Full ANN with PyTorch.vtt 9.5 KB
8. CNN - Convolutional Neural Networks/22. CNN Exercise Solutions.vtt 9.5 KB
3. Crash Course NumPy/7. Numpy Exercises - Solutions.vtt 9.3 KB
8. CNN - Convolutional Neural Networks/14. CIFAR-10 DataSet with CNN - Code Along - Part One.vtt 9.1 KB
8. CNN - Convolutional Neural Networks/9. Pooling Layers.vtt 8.8 KB
3. Crash Course NumPy/5. NumPy Operations.vtt 8.2 KB
7. ANN - Artificial Neural Networks/21. ANN - Exercise Overview.vtt 8.2 KB
5. PyTorch Basics/5. Tensor Operations - Part Two.vtt 7.8 KB
4. Crash Course Pandas/5. GroupBy Operations.vtt 7.6 KB
6. Machine Learning Concepts Overview/5. Evaluating Performance - Regression Error Metrics.vtt 7.4 KB
9. Recurrent Neural Networks/11. RNN Exercise.vtt 6.5 KB
6. Machine Learning Concepts Overview/6. Unsupervised Learning.vtt 6.2 KB
5. PyTorch Basics/7. PyTorch Basics - Exercise Solutions.vtt 6.0 KB
4. Crash Course Pandas/8. Pandas Exercises.vtt 5.2 KB
6. Machine Learning Concepts Overview/1. What is Machine Learning.vtt 5.2 KB
8. CNN - Convolutional Neural Networks/2. Understanding the MNIST data set.vtt 4.6 KB
5. PyTorch Basics/1. PyTorch Basics Introduction.vtt 4.2 KB
8. CNN - Convolutional Neural Networks/21. CNN Exercise.vtt 4.1 KB
5. PyTorch Basics/6. PyTorch Basics - Exercise.vtt 3.5 KB
11. NLP with PyTorch/1. Introduction to NLP with PyTorch.vtt 3.4 KB
8. CNN - Convolutional Neural Networks/10. MNIST Data Revisited.vtt 2.8 KB
8. CNN - Convolutional Neural Networks/1. Introduction to CNNs.vtt 2.5 KB
9. Recurrent Neural Networks/1. Introduction to Recurrent Neural Networks.vtt 2.5 KB
7. ANN - Artificial Neural Networks/1. Introduction to ANN Section.vtt 2.3 KB
3. Crash Course NumPy/6. Numpy Exercises.vtt 1.9 KB
4. Crash Course Pandas/1. Pandas Overview.vtt 1.7 KB
3. Crash Course NumPy/1. Introduction to NumPy.vtt 871 bytes
11. NLP with PyTorch/6. OUR MODEL FOR DOWNLOAD.html 588 bytes
12. BONUS SECTION THANK YOU!/1. BONUS LECTURE.html 532 bytes
2. COURSE OVERVIEW CONFIRMATION CHECK/1. DID YOU WATCH THE COURSE OVERVIEW LECTURE.html 157 bytes
11. NLP with PyTorch/6.1 Google Drive Link for another Model.html 143 bytes
10. Using a GPU with PyTorch and CUDA/1.3 NVIDIA CUDA Installation Page.html 142 bytes
7. ANN - Artificial Neural Networks/7.1 BackPropagation Explained 1.html 133 bytes
7. ANN - Artificial Neural Networks/7.2 BackPropagation Explained 1.html 133 bytes
10. Using a GPU with PyTorch and CUDA/1.4 PyTorch on Google Cloud Platform.html 130 bytes
10. Using a GPU with PyTorch and CUDA/1.5 PyTorch on Microsoft Azure.html 129 bytes
1. Course Overview, Installs, and Setup/2.2 Link for .yml environment file.html 127 bytes
8. CNN - Convolutional Neural Networks/16.1 Google Drive Download Link for CATS_DOGS .zip file.html 127 bytes
10. Using a GPU with PyTorch and CUDA/1.6 Google Collab with PyTorch.html 115 bytes
7. ANN - Artificial Neural Networks/7.1 Backpropagation - Great Theory Book!.html 112 bytes
7. ANN - Artificial Neural Networks/7.2 Backpropagation - Great Theory Book!.html 112 bytes
10. Using a GPU with PyTorch and CUDA/1.7 CUDA with PyTorch.html 108 bytes
10. Using a GPU with PyTorch and CUDA/1.2 PyTorch Official Install Page.html 101 bytes
10. Using a GPU with PyTorch and CUDA/1.1 PyTorch on AWS.html 92 bytes

Udemy - PyTorch for Deep Learning with Python Bootcamp (9.2019)

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