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UID:pretalx-pyconde-pydata-berlin-2023-WMAXSV@pretalx.com
DTSTART;TZID=CET:20230417T114000
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DESCRIPTION:AutoML\, or automated machine learning\, offers the promise of 
 transforming raw data into accurate predictions with minimal human interve
 ntion\, expertise\, and manual experimentation. In this talk\, we will int
 roduce AutoGluon\, a cutting-edge toolkit that enables AutoML for tabular\
 , multimodal and time series data. AutoGluon emphasizes usability\, enabli
 ng a wide variety of tasks from regression to time series forecasting and 
 image classification through a unified and intuitive API. We will specific
 ally focus on tasks on tabular and time series tasks where AutoGluon is th
 e current state-of-the-art\, and demonstrate how AutoGluon can be used to 
 achieve competitive performance on tabular and time series competition dat
 a sets. We will also discuss the techniques used to automatically build an
 d train these models\, peeking under the hood of AutoGluon.
DTSTAMP:20260711T203034Z
LOCATION:B05-B06
SUMMARY:AutoGluon: AutoML for Tabular\, Multimodal and Time Series Data - C
 aner Turkmen\, Oleksandr Shchur
URL:https://pretalx.com/pyconde-pydata-berlin-2023/talk/WMAXSV/
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