Optimization for Machine Learning
M2 IASD Apprentissage, Université Paris Dauphine-PSL, 2024-2025
Aim of the course
Study the main optimization techniques used in machine learning and data science, as well as their underlying principles.
Course material
Lecture notes (updated regularly)
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Board for lecture 1 (in French)
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Board for lecture 2 (in French)
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Board for lecture 4 (in French)
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Board for lecture 6 (in French)
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Board for lecture 7 (in French)
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Board for lecture 8 (in French)
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Tutorials and labs (in French)
Exercises on gradient descent (with solutions)
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Exercises on stochastic gradient (with solutions)
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Exercises on regularization (with solutions)
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Last year's exam (with solutions)
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Lab on gradient descent (with solutions)
Notebook
Lab on stochastic gradient (with solutions)
Notebook
Lab on subgradients (with solutions
Notebook
Lab on regularization (with solutions)
Notebook
Lab on momentum (with solutions)
Notebook
Materials on this page are available under Creative Commons
CC BY-NC 4.0 license.
La version française de cette page se trouve
ici.