MrTejas / ML-Algos

A collection of fundamental Machine Learning Algorithms Implemented from scratch along-with their applications for various ML tasks like clustering, thresholding, data analysis, prediction, regression and image classification.

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