madhug-nadig/Machine-Learning-Algorithms-from-Scratch

Implementing machine learning algorithms from scratch.

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Emerging

This project offers a clear, step-by-step implementation of foundational machine learning algorithms. It takes various datasets like stock prices, email content, or medical records, and shows how these algorithms process them to make predictions or find patterns. This resource is for students, educators, or practitioners who want to understand the inner workings of common ML techniques without relying on complex libraries.

389 stars. No commits in the last 6 months.

Use this if you want to learn, teach, or rigorously understand how core machine learning algorithms like Linear Regression, Naive Bayes, or K-Means clustering function at a fundamental level.

Not ideal if you need ready-to-use, highly optimized machine learning models for production applications or to analyze large datasets quickly.

Machine Learning Education Algorithm Study Data Science Learning Predictive Modeling Basics

No License Stale 6m No Package No Dependents

Maintenance 0 / 25

Adoption 10 / 25

Maturity 8 / 25

Community 25 / 25

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Stars

389

Forks

282

Language

Python

License

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