11. Regression models for Machine Learning

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Fig. 11.1 Photo by Beth Teutschmann on Unsplash

See also

Click the video above for a quick introduction to this section.

This part covers types of regression in the context of machine learning. Regression models can help determine the relationship between variables. This type of model can predict values such as length, temperature, or age, thus uncovering relationships between variables as it analyzes data points.

In this series of sections, you’ll discover the differences between linear and logistic regression, and when you should prefer one over the other.

In this group of sections, you will get set up to begin machine learning tasks, including configuring Visual Studio Code to manage notebooks, the common environment for data scientists. You will discover Scikit-learn, a library for machine learning, and you will build your first models, focusing on Regression models in this chapter.

See also

There are useful low-code tools that can help you learn about working with regression models. Try Azure ML for this task

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• 11.1. Tools of the trade
• 11.2. Managing data
• 11.3. Linear and polynomial regression
• 11.4. Logistic regression
• 11.5. Univariate linear regression