Introduction to Predictive Analytics in Python Data Camp

Overview

Context

In this Introduction to Predictive Analytics in Python course offered by Data Camp, you will learn how to build a logistic regression model with meaningful variables.

What you will learn during this course:

• You'll learn why variable selection is crucial for building a useful model. You'll also learn how to implement forward stepwise variable selection for logistic regression and how to decide on the number of variables to include in your final model.
• Now that you know how to build a good model, you should convince stakeholders to use it by creating appropriate graphs. You will learn how to construct and interpret the cumulative gains curve and lift graph.
• In a business context, it is often important to explain the intuition behind the model you built. Indeed, if the model and its variables do not make sense, the model might not be used. You'll learn how to explain the relationship between the variables in the model and the target by means of predictor insight graphs.