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Welcome to Chapter 9 lesson 2 of the full course on ‘Statistics for Data Science’, using Python! In this lesson we briefly explore basic concepts of Machine Learning. In particular we look at how we can use data to build a model that predicts new data. For categorical variables this is done by Logistic Regression. We will look at how to evaluate the performance of such models by looking at the Confusion Matrix, ROC curve, and others.

📚 Course Materials:

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🛠 Topics Covered:

What is Logistic Regression?
How to perform Logistic regression using Python?
How to visualise Logistic Regression?
How to quantify Logistic Regression?

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