PyTorch Exercises

This repository contains machine learning exercises I've completed while following the Daniel Bourkes 'Learn PyTorch for deep learning in a day. Literally.' guide.

Goal

My goal is to learn the fundamentals of PyTorch and apply them through practical examples. This project covers topics such as linear regression, building neural networks, and training models.

Projects

• Linear Regression: The first script, linear_regression.py, implements a simple linear regression model from scratch.
• Binary Classification: The script classification.py implements a small end-to-end classification example in PyTorch.
  It demonstrates creating a toy dataset, a lightweight feed-forward neural network, the complete training/validation loop, basic metrics (accuracy, loss).
• Multiclassification with IRIS dataset: This script iris.py is a classic, the "hello world" of multiclassification ml. It's a compact, end-to-end example using the Iris dataset and a feed-forward network implemented with torch.nn.Sequential.
• Fashion-MNIST Exploration: The script fashionMNIST.py introduces working with image datasets in PyTorch using the more difficult fashion-MNIST dataset. Right now it is a work in progress, but you can expect the first model to be ready soon.