Meet TransmogrifAI, Open Source AutoML powering Salesforce Einstein
Submitted by Rajdeep Dua (@rajdeepd) on Sunday, 14 April 2019
Session type: Tutorial
In this talk we will explain how TransmogrifAI - AutoML library on top of Apache spark helps build automated machine learning pipelines with features engineering, feature selection. It provides Automatic Model selection along with automated model hyper parameter tuning.
- Need of Multicloud and multi tenant models
- Lessons learned while building Einstein platform
- How traditional machine learning works
- Introducing TransmogrifAI
- Type Hierarchy
- Automatic Feature Engineering across text, categorical, numerical, spatial features
- Handling label leakage
- Autmatic Model Selection and hyper parameter tuning
- Models supported currently
- Uses cases being solved in production
Rajdeep is leading Industries Einstein team at Salesforce which is leveraging TransmogirfAI based data pipeline to solve ML problems across domains. He has overall 19 years of Software experience and has written 3 books in area on ML and DL.