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ML-algos-in-Jupyter

This repository contains a separate Jupyter Notebook for each Machine Learning algorithm implemented from scratch. The intricate math involved in every algorithm is explained using MarkDown and the code is written in Python.

The following are the algorithms implemented in this repository:

  1. Simple Linear Regression
  2. Multiple Linear Regression
  3. Logistic Regression - Binary Classification
  4. Regularized Logistic Regression - Binary Classification
  5. Logistic Regression for Multi-Class Classification
  6. Neural Network Learning - Feed-Forward and Back Propagation
  7. Support Vector Machines - For Spam Classification
  8. K-Means Clustering - For Image Compression
  9. Principal Component Analysis - For Dimensionality Reduction on Face Images