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UID:pretalx-euroscipy-2022-TXYGUK@pretalx.com
DTSTART;TZID=CET:20220829T103000
DTEND;TZID=CET:20220829T120000
DESCRIPTION:This tutorial will introduce how to leverage scikit-learn's pow
 erful\n**histogram-based gradient boosted regression trees** with various 
 loss functions\n(Least squares\, **Poisson** and the **pinball loss** for 
 quantile estimation) on a time\nseries forecasting problem. We will see ho
 w to leverage pandas to build **lag and\nwindowing features** and [scikit-
 learn](https://scikit-learn.org) time-series cross-validation tools and ot
 her\nmodel evaluation tools.
DTSTAMP:20260311T010151Z
LOCATION:HS 120
SUMMARY:Time Series Forecasting with scikit-learn's Quantile Gradient Boost
 ed Regression Trees - Olivier Grisel
URL:https://pretalx.com/euroscipy-2022/talk/TXYGUK/
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