Notebook tutorial: Build Product Recommendation Machine Learning Model with Feathr Feature Store

This Jupyter Notebook demonstrate how to use Feathr Feature Store to build a product recommendation machine learning model for a e-commerce website.

You will learn:
1. Define sharable features using Feathr API
2. Create a training dataset via point-in-time feature join with Feathr API
3. Materialize features to online store and then retrieve them with Feathr API
4. Register features to Feature Registry

00:00 Intro
00:41 Define Sharable Features
04:02 Define Feature Source
05:01 Define Simple Features
05:50 Define Window Aggregation Features
07:11 Define Derived Features
08:01 Build Training Dataset with Point-in-time Join Syntax
10:32 Materialize Features
13:00 Register Features

[MaternalAdvice]

Thank you!!! It was very informative. Please post more such tutorials.

[LaxmikanthR-nk]

Not able to materialize features which I have created through Feathr UI. Please provide documentation on how to use Feathr UI. Thanks