This repository provides a roadmap to becoming an artificial intelligence expert.
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ML-From-Scratch shares accessible NumPy implementations of machine learning models, from linear regression to deep learning.
About ML-From-Scratch
ML-From-Scratch is an open-source GitHub repository containing Python implementations of fundamental machine learning models and algorithms written from scratch with NumPy. The project states that its purpose is not to produce the most optimized or computationally efficient algorithms, but to present their inner workings in a transparent and accessible way. It covers supervised, unsupervised, reinforcement and deep learning implementations, ranging from linear regression to deep learning, and includes runnable example scripts.
Key features
- NumPy-based implementations of machine learning models written from scratch
- Covers supervised, unsupervised, reinforcement and deep learning algorithms
- Example scripts for polynomial regression and CNN digit classification
- Includes a GAN generating handwritten digits and a deep Q-network
- Also covers evolutionary neural networks, genetic algorithms and association analysis
- Installable by cloning the repository and running python setup.py install
Best for: Learners and developers who want to read readable, from-scratch NumPy code to understand how machine learning algorithms work internally.
Good for
- Explicit focus on accessibility and transparency over optimization
- Spans supervised, unsupervised, reinforcement and deep learning categories
- Includes runnable example scripts that print training output
Watch out for
- Project states it does not aim to provide optimized or computationally efficient algorithms
- Documented installation requires cloning the repository and running setup.py
ML-From-Scratch at a glance
- Category
- Education & Learning › AI Learning & Guides
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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ML-From-Scratch FAQ
What is the purpose of this project?
It presents the inner workings of fundamental machine learning models and algorithms in a transparent and accessible way, rather than producing the most optimized implementations.
How is it installed?
Clone the repository with git, change into the ML-From-Scratch directory, and run python setup.py install.
What kinds of algorithms are included?
The repository groups implementations into supervised learning, unsupervised learning, reinforcement learning and deep learning, from linear regression to deep learning.
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