This repository contains implementations of various machine learning algorithms from scratch in Python. Each algorithm is coded from the ground up, providing a deeper understanding of how these algorithms work under the hood. The implemented algorithms include:
Linear Regression Ridge Regression Lasso Regression Logistic Regression Naive Bayes Classifier Decision Trees Support Vector Machine (SVM) K-Nearest Neighbors (KNN) K-Means Clustering Gaussian Mixture Models (GMM)
Additionally, an example script demonstrating the usage of these algorithms on a sample dataset is provided. This example serves as a guide on how to utilize these implementations for real-world data analysis and modeling tasks.
I hope you find it helpful and make it better.