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1c3139 Lucas Gonthier 2026-06-30 12:04:21
Initial commit: course content (Machine Learning, MLOps) in EN and FR Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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# Machine Learning
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Foundations of machine learning: how to go from raw data to a trained, evaluated model.
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**Prerequisites:** basic Python, basic linear algebra and statistics.
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## Syllabus
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1. [Introduction](/en/Machine%20Learning/01%20Introduction)
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2. [General concepts](/en/Machine%20Learning/02%20General%20concepts)
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3. [Linear models](/en/Machine%20Learning/03%20Linear%20models)
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4. [Support Vector Machines](/en/Machine%20Learning/04%20Support%20Vector%20Machines)
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5. [Decision trees and ensemble methods](/en/Machine%20Learning/05%20Decision%20trees%20and%20ensemble%20methods)
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[MLOps](/en/MLOps) · [English home](/en)