Logistic regression is a type of regression analysis that helps in estimating the likelihood of an event to occur based on some given parameters. It is used as a classification technique with a binary outcome. The probabilities describing the possible outcomes of a single trial are modeled, as a function of the explanatory (predictor) variables, using a logistic function.

You have been already introduced to *Logisitc regression* in Chapter 5, *Uncovering Machine Learning*. In this chapter, you'll learn to:

- Build a logistic regression model with statsmodels
- Build a logistic regression model with SciKit
- Evaluate and test the model

We'll use the Titanic dataset, which was utilized in Chapter ...

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