How I used Polars to build built functime, a next gen ML forecasting library
Everybody knows Polars revolutionised the dataframe landscape, yet fewer realise that machine learning is next. Thanks to its extreme speed, we can speed up feature engineering by 1-2 orders of magnitude. The true gains, however, span across the whole ML lifecycle, with significantly faster batch inference and effortless scaling (no PySpark required!).
Add a best-of-the-class set of tools for feature extraction, model evaluation and diagnostic visualisations and you'll get functime: a next-generation library for ML forecasting. Though time-series practitioners are the primary audience, there's something for all data scientists. It's not just forecasting: it's about building the next generation of machine learning libraries.
