Automated Machine Learning with Erez Barak - #323
Published:Dec 6, 2019 16:32
•1 min read
•Practical AI
Analysis
This article from Practical AI features an interview with Erez Barak, a Partner Group Manager at Microsoft Azure ML. The discussion centers on Automated Machine Learning (AutoML), exploring its philosophy, role, and significance. Barak breaks down the AutoML process into three key areas: Featurization, Learner/Model Selection, and Tuning/Optimizing Hyperparameters. The interview also touches upon post-deployment use cases, providing a comprehensive overview of AutoML's application within the data science workflow. The focus is on practical applications and the end-to-end process.
Key Takeaways
- •AutoML is a key topic in the data science field.
- •The interview covers the end-to-end data science process with AutoML.
- •The discussion includes Featurization, Learner/Model Selection, and Tuning/Optimizing Hyperparameters.
Reference
“Erez gives us a full breakdown of his AutoML philosophy, and his take on the AutoML space, its role, and its importance.”