A Brief Introduction to Automated Machine Learning (AutoML)

Описание к видео A Brief Introduction to Automated Machine Learning (AutoML)

This video introduces the topic of Automated Machine Learning (AutoML) for beginners looking to understand or select an AutoML tool or library. This video (1) provides background information on machine learning and data science pipelines, (2) defines AutoML and major differences between AutoML tools and libraries, and (3) includes a survey of 24 open source AutoML solutions as of December 2023 aimed at helping potential users select an AutoML solution that might best work for their needs.

Video Links:
Urbanowicz et. al 2023 - Supporting information: https://arxiv.org/abs/2312.05461
STREAMLINE GitHub: https://github.com/UrbsLab/STREAMLINE
Auto-Keras GitHub: https://github.com/keras-team/autokeras
H20-3 AutoML GitHub: https://github.com/h2oai/h2o-3
MLme GitHub: https://github.com/FunctionalUrology/...
LAMA GitHub: https://github.com/sb-ai-lab/LightAutoML
FEDOT GitHub: https://github.com/aimclub/FEDOT
FLAML GitHub: https://github.com/microsoft/FLAML
ALIRO GitHub: https://github.com/EpistasisLab/Aliro
PYCARET GitHub: https://github.com/pycaret/pycaret
MLJAR-Supervised GitHub: https://github.com/mljar/mljar-superv...
Ludwig GitHub: https://github.com/ludwig-ai/ludwig/
TPOT GitHub: https://github.com/epistasislab/tpot/
Auto-Sklearn GitHub: https://github.com/automl/auto-sklearn
Auto-PyTorch GitHub: https://github.com/automl/Auto-PyTorch
GAMA GitHub: https://github.com/openml-labs/gama
Hyperopt-sklearn GitHub: https://github.com/hyperopt/hyperopt-...
Auto-WEKA GitHub: https://github.com/automl/autoweka
RECIPE GitHub: https://github.com/laic-ufmg/Recipe
ML-Plan GitHub: https://github.com/starlibs/AILibs
TransmogrifAI GitHub: https://github.com/salesforce/Transmo...
MLBox GitHub: https://github.com/AxeldeRomblay/MLBox
Xcessiv GitHub: https://github.com/reiinakano/xcessiv
Auto_ML GitHub: https://github.com/ClimbsRocks/auto_ml

Other Weblinks:
https://github.com/UrbsLab
http://ryanurbanowicz.com/

Chapters:
0:00 Introduction and Machine Learning Background
10:24 Automated Machine Learning (AutoML) Basics
12:50 Survey of AutoML Tools/Libraries
15:52 Considerations for Choosing an AutoML Solution
26:18 Summary

Комментарии

Информация по комментариям в разработке