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Broadly speaking, Machine Learning refers to the automated identification of patterns in data.
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FREE
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Description
As such it has been a fertile ground for new statistical and algorithmic developments. The purpose of this course is to provide a mathematically rigorous introduction to these developments with emphasis on methods and their analysis.
You can read more about Prof. Rigollet’s work and courses on his website .
Course content
- Introduction Unlimited
- Binary Classification Unlimited
- Concentration Inequalities Unlimited
- Fast Rates and VC Theory Unlimited
- The VC Inequality Unlimited
- Covering Numbers Unlimited
- Chaining Unlimited
- Convexification Unlimited
- Boosting Unlimited
- Support Vector Machines Unlimited
- Gradient Descent Unlimited
- Projected Gradient Descent Unlimited
- Mirror Descent Unlimited
- Stochastic Gradient Descent Unlimited
- Prediction with Expert Advice Unlimited
- Follow the Perturbed Leader Unlimited
- Online Learning with Structured Experts Unlimited
- Stochastic Bandits Unlimited
- Prediction of Individual Sequences Unlimited
- Adversarial Bandits Unlimited
- Linear Bandits Unlimited
- Blackwell’s Approachability Unlimited
- Potential Based Approachability Unlimited
Instructor
Massachusetts Institute of Technology
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