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Chapter 2 - Supervised Learning

Table of contents

  1. 2.0.1 - Introduction
  2. 2.1 Regression
    1. 2.1.1 Linear regression
    2. 2.1.2 Regularized Linear Models
    3. 2.1.3 Significance of Parameters
    4. 2.1.4 Nonlinear Regression
      1. 2.1.4.1 Neural Networks
  3. 2.2 Classification
    1. 2.2.1 Linear Classification
      1. 2.2.1.1 Rosenblatt's perceptron
      2. 2.2.1.2 Support Vector Machines
    2. 2.2.2 Neural Networks (for Classification)
    3. 2.2.3 Bayes and Naive Bayes Classification
      1. 2.2.3.1 Bayes Classification
      2. 2.2.3.2 Naive Bayes Classification