In this video we cover the basics of the most simple machine learning model K-Nearest Neighbors. I also explain what a hyperparameter is and how to use a grid search in scikit-learn to test multiple models. Finally I cover machine learning model evaluation metrics such as accuracy, recall, precision, and more. We wrap up with ROC AUC curves and how to compare the performance of multiple models in one visualization.
Code and data can be found by visiting my website: https://kelseyemnett.com/2021/05/15/k...
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