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4th AutoML
Date: September 2nd - 6th 2024 Place: Hannover, Germany
Date: September 2nd - 6th 2024 Place: Hannover, Germany
Motivation
Motivation
By increasing the efficiency of ML-application development and supporting users in crucial design decisions, AutoML became a key approach in the toolkit of many developers and researchers. Although there is an exponentially growing interest in AutoML, AutoML is so far only rarely taught at universities and there is a large gap between the current state of the art in research and disseminated knowledge. The AutoML Summer School will cover core topics of AutoML, covering basics, state-of-the-art approaches and hands-on sessions. Enthusiastic AutoML experts will present their diverse views on AutoML to ML practitioners, developers, research engineers, researchers and students.
Key Features
Key Features
Learn from world-leading
experts in AutoML
Hands-on sessions with
open-source packages
Talk to people --
Increase your network
Social Events
Keynote Speakers by
Keynote Speakers by
Professor of ML & AI
at TU Darmstadt
Topic: AutoML and Neural Architecture Search
Professor of ML
at Technical University Nürnberg
Topic: Modern Hyperparameter Optimization
Professor of Embedded Systems
at University of Tübingen
Topic: Energy-efficient Machine Learning in Hardware
Applied Scientist at AWS AI
Topic: Foundational Models and AutoML for Time Series Forecasting
Professor at the Data Science & AI Department of Monash University (Melbourne)
Topic: Optimization
Invited Speakers
Invited Speakers
Research Engineer at
Google Deepmind
Topic: Practical Bayesian Optimization for Hyperparameter Optimization
Centre of Solar Energy and Hydrogen Research Baden-Württemberg
Topic: Hands-On Experience from Real-World Use Cases
Thomas Meißner
Kaggle Master. Senior Data Scientist at SumUp
Topic: Hands-On Experience with BlueCast
Basic Lectures By
Basic Lectures By
Professor of ML
at University of Freiburg /
ELLIS Institute Tübingen
Topic: AutoML and foundational Models
Professor of Statistical Learning and Data Science
at Ludwig-Maximilians-University Munich
Topic: Hyperparameter Optimization
Professor and Thomas Bayes Fellow
at Ludwig-Maximilians-University Munich
Topic: AutoML Systems
Tutorials by
Tutorials by
Danny Stoll and Neeratyoy Mallik
University of Freiburg
Topic: NEPS
Carolin Benjamins
Leibniz University Hannover
Topic: SMAC & Benchmarking
Daphne Theodorakopoulos
Leibniz University Hannover
Topic: Analysing Multi-Objective AutoML
Theresa Eimer and Andre Biedenkapp
Leibniz University Hannover and University of Freiburg
Topic: AutoRL
Christoph Gerum
University of Tübingen
Topic: HANNAH
Lennart Purucker
University of Freiburg
Topic: Automated Data Science / TabPFN
Ivo Rapant
University of Freiburg
Topic: Quicktune
In the meantime, join our AutoML MOOC
In the meantime, join our AutoML MOOC
... available for free at ai-campus.org and a perfect opportunity for getting a basic background in AutoML before attending our AutoML Fall school.
Organized by Members of
Organized by Members of
Visibility Support by
Visibility Support by
Header image and logo under CC BY-SA 4.0 from ai-campus.org and automl.org; Illustrations by https://undraw.co/ Other images sourced from https://creativecommons.org/ under the CC BY 4.0 license.
The welcome dinner and christmas market footage is lincensed under the Creative Commons Attribution-Share Alike 3.0 Unported license.
The welcome dinner and christmas market footage is lincensed under the Creative Commons Attribution-Share Alike 3.0 Unported license.
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