PyTorch Fundamentals: Your First Steps into Hands-on Deep Learning

Overview

Introduction to PyTorch fundamentals, covering tensor initialization, operations, indexing, and reshaping.

Install Dependencies

pip install -r requirements.txt

If you're installing torch with CUDA support, make sure to use the correct installation command from PyTorch's official website, as some versions require a specific installation method.

Contents

• What are Tensors?
• Tensor Initialization
• Common Tensor Initialization Methods
• Tensor Type Conversion
• Converting Between NumPy Arrays and Tensors
• Tensor Mathematics and Comparison Operations
• Matrix Multiplication and Batch Operations
• Broadcasting and Other Useful Operations
• Tensor Indexing
• Tensor Reshaping

Code Notebook

Dive into the hands-on examples in this interactive Jupyter notebook.

Blog Post

Read the full breakdown and insights in the accompanying blog post.

Contribution

• Fork the repo
• Create a new branch
• Make your changes
• Submit a Pull Request

License

This project is licensed under MIT License