When optimizing an ML model there are a variety of strategies to improve generalization from the training data. We can add a complexity penalty to the loss function, and we can evaluate the loss function on validation data.
Slides for regularization video (PDF)
Notebook for validation (partially complete)
Notebook for lasso (no partially complete version)
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For attribution, please cite this work as
Loftus (2021, March 1). Neurath's Speedboat: Regularization and validation. Retrieved from http://joshualoftus.com/ml4ds/06-regularization/
BibTeX citation
@misc{loftus2021regularization,
author = {Loftus, Joshua},
title = {Neurath's Speedboat: Regularization and validation},
url = {http://joshualoftus.com/ml4ds/06-regularization/},
year = {2021}
}