Machine Learning

# Machine Learning

Foundations of machine learning: how to go from raw data to a trained, evaluated model.

**Prerequisites:** basic Python and the [Mathematics](/en/Mathematics) course (linear algebra, probability, statistics).

## Syllabus

1. [Introduction](/en/Machine%20Learning/01%20Introduction)
2. [General concepts](/en/Machine%20Learning/02%20General%20concepts)
3. [Probabilistic formulation](/en/Machine%20Learning/03%20Probabilistic%20formulation)
4. [Linear regression](/en/Machine%20Learning/04%20Linear%20regression)
5. [Linear classification](/en/Machine%20Learning/05%20Linear%20classification)
6. [Multilayer neural networks](/en/Machine%20Learning/06%20Multilayer%20neural%20networks)
7. [Decision trees and ensemble methods](/en/Machine%20Learning/07%20Decision%20trees%20and%20ensemble%20methods)

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