Machine Learning

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

Prerequisites: basic Python, basic linear algebra and statistics.

Syllabus

1. Introduction
2. General concepts
3. Linear models
4. Support Vector Machines
5. Decision trees and ensemble methods

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