/Learning-PyTorch

Explore my journey of learning PyTorch through a series of hands-on projects! This GitHub repository showcases my progress in mastering PyTorch fundamentals, including linear regression, multi-class classification, non-linear activation functions, CNN for Fashion MNIST, transfer learning, and model deployment.

Primary LanguageJupyter Notebook

PyTorch Notebooks

This repository contains a collection of Jupyter notebooks that I created while learning PyTorch. I used the following resource to learn PyTorch:

The notebooks cover various topics and tasks related to PyTorch, including linear regression, multi-class classification, CNN, transfer learning, and more.

Notebooks

  1. 00_pytorch_fundamentals.ipynb - An introduction to PyTorch fundamentals.
  2. 01_pytorch_workflow_linear_regression_v1.ipynb - Linear regression using PyTorch (Version 1).
  3. 01_pytorch_workflow_linear_regression_v2.ipynb - Linear regression using PyTorch (Version 2).
  4. 02_pytorch_multi_class_classification.ipynb - Multi-class classification with PyTorch.
  5. 02_pytorch_multi_layer_binary_classification.ipynb - Binary classification with multiple layers in PyTorch.
  6. 02_pytorch_multi_layer_non_linear_classification.ipynb - Non-linear classification with multiple layers in PyTorch.
  7. 02_pytorch_multi_layer_regression.ipynb - Multi-layer regression using PyTorch.
  8. 02_pytorch_non_linear_activation_functions.ipynb - Exploring non-linear activation functions in PyTorch.
  9. 02_pytorch_non_linear_spiral_classification.ipynb - Non-linear spiral classification with PyTorch.
  10. 02_pytorch_simple_binary_classification.ipynb - Simple binary classification using PyTorch.
  11. 03_pytorch_fashion_mnist_cnn.ipynb - Fashion MNIST classification using CNN in PyTorch.
  12. 03_pytorch_fashion_mnist_linear.ipynb - Fashion MNIST classification using linear models in PyTorch.
  13. 03_pytorch_fashion_mnist_non_linear.ipynb - Fashion MNIST classification using non-linear models in PyTorch.
  14. 03_pytorch_fashion_mnist_resnet50.ipynb - Fashion MNIST classification using ResNet50 in PyTorch.
  15. 04_pytorch_custom_dataset.ipynb - Working with custom datasets in PyTorch.
  16. 05_pytorch_transfer_learning.ipynb - Transfer learning with PyTorch.
  17. 06_pytorch_experiment_tracking.ipynb - Experiment tracking with PyTorch.
  18. 07_pytorch_vision_transformer.ipynb - Vision Transformer (ViT) implementation in PyTorch.
  19. 08_pytorch_model_deployment.ipynb - Model deployment using PyTorch.
  20. 09_pytorch_quick_pytorch_2.ipynb - Quick introduction to PyTorch 2.0.

Learning Resource

I used the following resource to learn PyTorch:

Acknowledgments

Special thanks to Daniel Bourke (Github username: mrdbourke) for providing valuable learning material and code examples. You can find his repository on PyTorch Deep Learning here: PyTorch Deep Learning.

Feel free to explore the notebooks and utilize the resources mentioned above to enhance your PyTorch skills. Happy learning!

Note: If you plan to use any part of this repository or the models, please adhere to the respective licenses and terms of use.