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This bootcamp is an invitation to use logistic regressions and statistical tests for binary classification problems

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1. What is machine learning and logistic regressions?

2. A look at R.

3. Formal description of the logistic regressions.

4. Implementation of logistic regressions to detect plausibility of reviews.

5. Advanced aspects of logistic regressions.

 

 

Syllabus

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1. Introduction

   • What is machine learning and logistic regressions

   • Mathematical notions and probability elements

   • Probability elements

2. Installation of R, R Studio and Packages required for Ridge Regression

   • Installation of R and Rstudio

   • For Windows

   • For Mac

   • For Ubuntu

   • For other versions of Linux

   • Installing R Packages

3. Logistic regression

   • Maximum likelihood

   • Binary classification and logistic regression

   • Geometric and probabilistic interpretation

4. Favorable review classifier

5. Selected Topics in Linear Regressions

   • Gradient method

   • Ridge regularization

   • Maximuma posteriori

   • Confidence intervals