README.md

Machine Learning Journey

This repository contains:

1. My notes on the book "Mathematics for Machine Learning" (PDF and HTML)
2. Many different machine learning models, either built from scratch, using only numpy, or using models from sklearn
3. An automatic differentiation system (MLlib.py) to create trainable neural networks.
4. Usage of the Automatic differentiation system for different tasks, like
   1. Digit Classification (Digits.ipynb)
   2. Iris dataset classification (Iris.ipynb)
   3. Embedding (Embed.ipynb)
   4. Reccurent Neural Network (RNN.ipynb)
   5. Illustration of Automotic differentiation (AutoDiff.ipynb)
5. Data Narratives on a few datasets