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Logistic Regression Workshop

Welcome to this workshop about Logistic Regression. We will cover the conceptual and mathematical foundations of the logistic regression classifier; take a look at a simple example to learn how to implement logistic regression models in Python; finally, we will cover some performance evaluation techniques and discuss the advantages and limitations of logistic regression.

Software Prerequisites

Make sure you have the packages math, numpy, pandas, matplotlib, seaborn, and sklearn installed. You can use pip or conda to install them.

Directory Structure

  • README.md - this very same README file briefly introducing you to the workshop
  • workshop.ipynb - the workshop itself is contained here
  • diabetes.csv - the csv file with the data used in the workshop

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First draft of logistic regression workshop for DSS

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