PyTorch Zero to Mastery

About:
This repository serves as a comprehensive guide to learning PyTorch from scratch. It covers essential concepts, practical implementations, and advanced techniques, making it a perfect resource for beginners and intermediate learners. The repository is regularly updated with new content to stay current with PyTorch advancements.

Structure

1. Installation

• Guides users through installing PyTorch on different platforms.

2. Check Installation

• PyTorch Version: Verifies the installed version.
• CUDA Compatibility: Ensures GPU support is correctly set up.

3. Tensors

Covers the fundamentals of tensors and their operations:

• Tensor Operations
• Matrix Operations
• Advanced Operations
• Reshaping and Slicing
• Reductions & Aggregations
• Comparison Operations
• Broadcasting
• Random Tensor Operations
• Gradient Operations (autograd)
• Saving & Loading Tensors

Outcome: Provides a solid foundation for working with data in PyTorch.

4. Neural Networks

Explores building and training neural networks:

• Model Design
• Training Loops
• Creating Custom Datasets

Outcome: Equips users to build and train models for various machine learning tasks.

5. Evaluation

Covers best practices for evaluating machine learning models using PyTorch.

6. Use GPU

Teaches how to leverage GPU acceleration in PyTorch for faster computations.

Technologies Used

• PyTorch, CUDA, Python.

Key Takeaways

• Guides learners through PyTorch’s core concepts and methods step by step.
• Includes practical examples for real-world applications.
• Regularly updated with new content and techniques.

Explore the repository here: PyTorch Zero to Mastery