Notebook tutorial: Build Product Recommendation Machine Learning Model  with Feathr Feature Store
Channel: Feathr Feature Store
Date: 01/08/2022

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

Notebook: https://github.com/linkedin/feathr/blob/main/docs/samples/product_recommendation_demo.ipynb

Github Repo: https://github.com/linkedin/feathr

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