TRUSTED LEARNING LINKS

Use ML Atlas for intuition. Use these for depth and practice.

These resources were selected because they are authoritative, hands-on, interactive or open source. External links open in a new tab.

AUTHORITATIVE

Courses & documentation

Animated videos, interactive visualizations and hands-on exercises covering regression, classification, data, neural networks and real-world ML.

Reference-quality documentation for linear models, SVM, nearest neighbours, trees, ensembles, clustering, PCA, preprocessing and evaluation.

Free short courses in Python, Intro to Machine Learning, Intermediate ML, feature engineering, explainability and real datasets.

A classic in-browser neural-network playground for experimenting with datasets, features, learning rate, regularization and hidden layers.

Visual and interactive essays from Machine Learning University covering core concepts such as regression, ROC/AUC and neural networks.

OPEN SOURCE REFERENCES

Large collection of machine-learning algorithms implemented and demonstrated directly in the browser.

Open-source code behind interactive machine-learning explanatory articles.

Interactive curriculum patterns including guided paths, quizzes, glossary links, labs and local progress.

JavaScript visualizations inspired by Artificial Intelligence: A Modern Approach.

Interactive machine-learning and deep-learning demos designed to develop intuition in the browser.