Use AutoML to create high-quality models with just a few clicks
summary
Amazon SageMaker Autopilot automatically explores feature engineering, trains hundreds of models with hyperparameter tuning, and outputs runnable EDA notebook and model-candidate notebooks showing exact transformations and algorithms used. It integrates with Redshift/Athena, optimizes instance size for cost, and claims real gains: a user moves a model from 76% to 91% accuracy. Vendors (Domo, Sisense) embed Autopilot for production use, yielding higher traffic and 2X time to market.
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chapters (16)
- 0:00Introduction
- 0:35Agenda
- 0:56Mission of AutoML
- 2:13What is tabular data
- 3:06Use cases
- 4:11Machine learning life cycle
- 10:28AutoML core features
- 12:43AutoML Transparent
- 13:49Notebooks
- 15:01Demo
- 15:37Create an experiment
- 17:56Data set walkthrough
- 20:38Data exploration notebook
- 27:46Freddys
- 29:09Skullcandy
- 29:59Resources
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