Yellowbrick is mainly designed to visualize and Diagnose the machine learning models. It is a visualization suite built on top of Scikit-Learn and Matplotlib. It helps in the model selection process, hyperparameter tuning, and algorithm selection.

Yellowbrick calls an API using the visualizer which is a scikit-learn estimator, the visualizer learns from data by creating the visualization of the workflow of the model selected. These visualizations allow us to draw insights into the model selection process.

In this article, we will explore different types of visualizations that are provided by Yellowbrick and how we can create them according to our requirements.

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