Welcome to the PyTorch Zero to Mastery repository! This repository contains Jupyter notebooks designed to take you from the basics of PyTorch to advanced deep learning techniques.
Modules 00 - PyTorch Fundamentals What does it cover?
Many fundamental PyTorch operations used for deep learning and neural networks. 01 - PyTorch Workflow What does it cover?
Provides an outline for approaching deep learning problems and building neural networks with PyTorch. 02 - PyTorch Neural Network Classification What does it cover?
Uses the PyTorch workflow from 01 to go through a neural network classification problem. 03 - PyTorch Computer Vision What does it cover?
Let’s see how PyTorch can be used for computer vision problems using the same workflow from 01 & 02. 04 - Custom Datasets What does it cover?
How do you load a custom dataset into PyTorch? Also, we’ll be laying the foundations in this notebook for our modular code (covered in 05). Future Updates More modules and notebooks will be added in the future. Stay tuned!
Getting Started Clone the repository: git clone https://github.com/yourusername/pytorch-zero-to-mastery.git
Navigate to the repository directory: cd pytorch-zero-to-mastery
Install the required dependencies: pip install -r requirements.txt
Open the Jupyter notebooks: jupyter notebook
Contributing Feel free to fork this repository, make improvements, and submit pull requests. Contributions are welcome!