In this webinar, Vladyslav Khizhanov, discusses how to build optimal machine learning-based prediction models with our Auger.AI Automated Machine Learning Service.
The following topics are covered in the discussion:
Sizing your instances based on data size
Choosing algorithms (i.e. restricting search) based on data dimensionality (rows and columns) and data distribution (edited)
Restricting search based on explainability
Restricting search based on prediction runtime deployment size and speed
Choosing the appropriate accuracy metric to optimize for
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