This repository contains implementations of fundamental Machine Learning algorithms written entirely from scratch in C and C++ — without using external ML libraries.
The goal is to understand how ML works under the hood by building everything step by step.
- Implementations in both C and C++
- No external ML frameworks (pure logic)
- Well-structured, modular, and beginner-friendly
- Focus on performance and clarity
- Learning resource for students and developers
- Linear Regression
- Logistic Regression
- K-Nearest Neighbors (KNN)
- Naive Bayes
- Decision Trees
- Support Vector Machines (SVM)
- K-Means Clustering
- Neural Networks (basic)
(More to be added...)