PyTorch Learning Notebooks

This repository contains three structured Jupyter notebooks designed to teach the fundamentals of deep learning with PyTorch.
The content progresses from basic tensor operations to building and training a full neural network.

Included Notebooks

1. Tensor Operations.ipynb – Introduction to tensors and PyTorch basics
2. Custom DataLoader.ipynb – Building your own Dataset and DataLoader
3. Model Creation and Training.ipynb – Creating, training, and validating a neural network model

Each notebook is self-contained and can be studied independently.

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🚀 Installation & Setup

Follow these steps to run all notebooks without issues.

1 Install Python

Download from the official website:

https://www.python.org/downloads/

Make sure to enable “Add Python to PATH” (Windows only).

Linux / MacOS:

sudo apt install python3 python3-pip     # Linux
brew install python3                     # MacOS

2 Install Required Packages

Open a terminal and run:

pip install torch torchvision torchaudio
pip install matplotlib numpy
pip install jupyter

If you want GPU support, choose the correct CUDA version at: https://pytorch.org/get-started/locally/

You can use Google colab to run jupyter notebooks or install jupyter locally to run notebooks locally.