Machine Learning in Python: Regression

3 tutorials

In the Exploratory Data Analysis with Python module, we honed your pandas skills, specifically focusing on using it for Exploratory Data Analysis (EDA). In this module, we’ll build on those skills and start looking at analyzing entire datasets from start to finish, beginning with getting the data, conducting some basic analyzes on it, and using machine learning to create a model from the data.

Our machine learning tool of choice will be scikit-learn, a popular Python library for machine learning. Specifically, we will explore linear and logistic regression, two simple but very powerful algorithms that will make a good starting point for exploring the world of Machine Learning.

Note that this module assumes you have some background in Python, particularly regarding EDA. If these are completely new to you, go through the following on StackUp Learn modules first:

Helpful prior knowledge


Learning Outcomes

By the end of this module, learners will be able to:

  • Reinforce your EDA skills on real datasets
  • Learn the fundamentals of machine learning
  • Experience using scikit-learn to solve machine learning problems using regression
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