Polars Feature Engineering: Lags, Diffs, and Percent Changes

This post discusses essential feature engineering techniques for machine learning, focusing on lags, differences, and percent changes, particularly in the context of predicting stock prices or sales. The author emphasizes that simple inputs like 'Today's Price' are insufficient for effective predictions, highlighting the importance of more complex features derived from those inputs.