Machine Learning Algorithms from Scratch

This repository contains implementations of various machine learning algorithms from scratch. Each algorithm is coded in Python without relying on external libraries to provide a clear understanding of the underlying principles.

Implemented Algorithms:

1. K-Nearest Neighbors (KNN)
2. Logistic Regression
3. Multi-Layer Perceptron (MLP)
   • Implementation for both regression and classification tasks
4. Principal Component Analysis (PCA)
5. Gaussian Mixture Model (GMM) Clustering
6. Ensemble Methods:
   • Bagging
   • Stacking
   • Adaboost
   • Gradient Boosted Regression Trees (GBRT)
   • Random Forests

Getting Started:

Clone the repository to your local machine:

git clone https://github.com/MrTejas/ML-Algos.git
cd ML-Algos