How to use Seaborn Data Visualization for Machine Learning

Last Updated on August 19, 2020

Data visualization provides insight into the distribution and relationships between variables in a dataset.

This insight can be helpful in selecting data preparation techniques to apply prior to modeling and the types of algorithms that may be most suited to the data.

Seaborn is a data visualization library for Python that runs on top of the popular Matplotlib data visualization library, although it provides a simple interface and aesthetically better-looking plots.

In this tutorial, you will discover a gentle introduction to Seaborn data visualization for machine learning.

After completing this tutorial, you will know:

• How to summarize the distribution of variables using bar charts, histograms, and box and whisker plots.
• How to summarize relationships using line plots and scatter plots.
• How to compare the distribution and relationships of variables for different class values on the same plot.

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