eriklindernoren/ML-From-Scratch
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
From the publisher
README & documentation
Source previewRead the project’s overview, installation instructions and usage examples. The original README is the source of truth.
Python implementations of some of the fundamental Machine Learning models and algorithms from scratch. The purpose of this project is not to produce as optimized and computationally efficient algorithms as possible but rather to present the inner workings of them in a transparent…
Read the full README ↗ · Preview checked 2026-10-31T23:52:28.042Z
Inside the original README — Document outline
- Machine Learning From Scratch
- About
- Table of Contents
- Installation
- Examples
- Polynomial Regression
- Classification With CNN
- Density-Based Clustering
- Generating Handwritten Digits
- Deep Reinforcement Learning
- Image Reconstruction With RBM
- Evolutionary Evolved Neural Network
Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.
Links from the README
References supplied by the publisher, not independently verified endorsements. Check the destination before downloading files or entering credentials.
Documentation belongs to its respective authors. Reported project/model license: MIT. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
What this repository does
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Repository facts
- Owner
- eriklindernoren
- Primary language
- Python
- Stars
- 33,189
- Forks
- 5,520
- Open issues + pull requests
- 82
- License
- MIT
- Archived
- No
- Default branch
- master
- Created
- 2017-02-05T12:11:23.000Z
- Last push
- 2023-10-15T06:05:06.000Z
Topics and intended use
Owner-supplied topics: data-mining, data-science, deep-learning, deep-reinforcement-learning, genetic-algorithm, machine-learning, machine-learning-from-scratch
Review the README for scope, installation, examples and limitations. We do not run repository code or certify it.
Evaluate before installing
Review licensing and dependencies, inspect recent commits and unresolved issues, and test in an isolated environment before production use. Stars and forks alone cannot answer these questions.
Source and freshness
Source: GitHub. Metadata observed 2026-10-31T12:19:22.904Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
Related repositories
EbookFoundation/free-programming-books
donnemartin/system-design-primer