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All topics
Topic II
Probabilistic Machine Learning
Optimization methods and linear regression models.
Chapter 8 — Optimization
8.1
Introduction to Optimization
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8.2
First-Order Methods
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8.3
Second-Order Methods
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8.4
Stochastic Gradient Descent
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8.5
Constrained Optimization
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8.6
Proximal Gradient Method
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8.7
Bound Optimization
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8.8
Black-Box Derivative-Free Optimization
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Chapter 11 — Linear Regression
11.1
Introduction to Linear Regression
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11.2
Least Squares Linear Regression
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11.3
Ridge Regression
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11.4
Lasso Regression
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11.5
Regression Splines
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11.6
Robust Linear Regression
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11.7
Bayesian Linear Regression
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