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* remove redundant doc and add tutorial * add demos for pydata2023 * Update pydata23 docs * remove redundant notebooks * Move tutorial notebooks to notebook folder * update readme and notebook links * update notebook links * update links * update readme --------- Co-authored-by: Li Jiang <lijiang1@microsoft.com> Co-authored-by: Li Jiang <bnujli@gmail.com>
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3.1 KiB
KDD 2022 Hands-on Tutorial - Automated Machine Learning & Tuning with FLAML
Session Information
Date: August 16, 2022 Time: 9:30 AM ET Location: 101 Duration: 3 hours
For the most up-to-date information, see the SIGKDD'22 Program Agenda
Tutorial Slides
What Will You Learn?
- What FLAML is and how to use it to find accurate ML models with low computational resources for common machine learning tasks
- How to leverage the flexible and rich customization choices to:
- Finish the last mile for deployment
- Create new applications
- Code examples, demos, and use cases
- Research & development opportunities
Session Agenda
Part 1
- Overview of AutoML and FLAML
- Task-oriented AutoML with FLAML
- ML.NET demo
- Tune user defined functions with FLAML
- Q & A
Part 2
- Zero-shot AutoML
- Time series forecasting
- Natural language processing
- Online AutoML
- Fair AutoML
- Challenges and open problems