This course covers the basics of feature stores and their advantages. It also includes a small demo on using Tecton, one of the platforms that allow you to utilize a Feature Store to accelerate your deployed machine learning model to make it more efficient and quicker.
Accelerating Machine Learning with a Feature Store
Introduction to Feature Stores and their Applications in Machine Learning
18 Tutorials
0 Exercises
Intermediate Level
100% Online
Self-paced
Our Alumni Work At
About this course
Contributors & Instructors
K
Kevin Stumpf
CTO & Founder, Tecton
D
David Hershey
Senior Solutions Architect, Tecton
What you will learn?
This course will teach you why feature stores are useful for real-time machine learning models and how they help you streamline your models and make the distribution of work across teams easier. You will learn about Tecton, a platform that enables you to implement a feature store for a deployed ML model.
Course Content
1. Introduction
4
Session and Speaker Overview
Operational Machine Learning
Uber’s Michelangelo Platform
What is A Feature Store
2. Problems Solved by Feature Stores
4
Extracting and Serving Features from Data
Removing Need for Repetitive Pipeline Building
High Barrier to Entry
Data Issues Break Models in Production
3. Deeper Dive into Feature Stores
4
Components of Feature Stores
Using Feature Store in ML Lifecycle
How Feature Stores Help ML Teams
Getting Started with a Feature Store
4. Demo of Tecton
6
Introduction
Tecton's UI
Problem Statement and Scenario
Creating a New Feature
Using Feature Store to Train a Model
Monitoring the Model, Tecton Support and Wrapping Up
