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ML01 · Machine Learning Foundations

A free, illustrated L1 course of 10 modules in the Machine Learning track. Modules include: What learning from data means; Data splits and the generalization gap; k-nearest neighbors.

ML01 L1 · Core 10 modules · about 40 lessons 10 of 10 modules live

Part of the Machine Learning track. Ships in Ring 1 (Foundation) of the roadmap.

Modules

1. What learning from data means Live · 4 lessons
2. Data splits and the generalization gap Live · 4 lessons
3. k-nearest neighbors Live · 4 lessons
4. Linear regression as a learning algorithm Live · 4 lessons
5. Gradient descent from scratch Live · 4 lessons
6. Logistic regression and classification Live · 4 lessons
7. Evaluation metrics Live · 4 lessons
8. Overfitting, bias and variance Live · 4 lessons
9. Regularization and validation Live · 4 lessons
10. A full project from raw data to report Live · 4 lessons

Signature illustrations

The pictures a learner should still see in their head a year later:

Decision-boundary explorers, training and validation curves, bias-variance decomposition, anatomy of a confusion matrix, ROC and precision-recall curves built point by point.

Status

10 of 10 modules are written and live. The rest follow in Ring 1.

Every lesson will follow the same twelve-part blueprint with at least three purpose-made figures. Watch the repository to hear when modules ship, or help write and review it.