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Feature Selection in Machine Learning

In this short video, Max Margenot gives an overview of selecting features for your model. He goes over the process of adding parameters to your model while avoiding overfitting. He also discusses general tools for evaluating the quality of different features, many contained in packages like scikit-learn, and covers methods of testing the various features in your algorithm.

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2 responses

Thanks for the video, Max and Phoebe and great insights!

Thanks. Very helpful for me. Hoping you’ll do more of these, and perhaps longer tutorials or lessons as well. If you or anyone else has any tips on how/where to learn more about ML that could be used directly within the Q environment (or via Self Serve Data) that would be super helpful!