Feature Store for Machine Learning: Curate, discover, share and serve ML features at scale

J, Jayanth Kumar M

ISBN 10: 1803230061 / ISBN 13: 9781803230061

Published by Packt Publishing, 2022

Somewhat damaged. May have bumped corner, torn dust cover, folded pages, light dust soil, remainder mark, price sticker, other damage, or be bent. 99% of orders arrive in 4-10 days. Discounted shipping on multiple books. Seller Inventory # mon0001306312

Synopsis:

Learn how to leverage feature stores to make the most of your machine learning models

Purchase of the print or Kindle book includes a free PDF eBook

What’s inside

• Insights into the significance of feature stores in the ML life cycle
• Easy-to-follow techniques to show you how features can be shared, discovered, and re-used
• Instructions to make features available for online models during inference

You’ll get the most out of this book if

• You have a solid grasp on machine learning basics, but need a comprehensive overview of feature stores to start using them
• You’re a data/machine learning engineer or a data scientist who builds machine learning models for production systems in any domain
• Your role includes supporting data engineers in productionizing ML models
• You're a platform engineer who builds data science (ML) platforms for your organization

What your journey will look like

This book will show you how to utilize feature stores to their fullest potential, saving you a lot of time and effort by teaching you how to use feature stores to share and reuse each other's work and expertise.

You'll be able to implement practices that help in eliminating reprocessing of data, providing model-reproducible capabilities, and reducing duplication of work, thus improving the time to production of the ML model.

While this ML book offers some theoretical groundwork for developers who are just getting to grips with feature stores, there's plenty of practical know-how for those ready to put their knowledge to work.

Some of the things you’ll learn from this book

• The significance of feature stores in a machine learning pipeline
• How to curate, store, share and discover features using feature stores
• The different components and capabilities of a feature store
• How to use feature stores with batch and online models
• Accelerating your model life cycle and reducing costs
• Effective deployment of your first feature store for production use cases

Table of Contents

1. An Overview of the Machine Learning Life Cycle
2. What Problems Do Feature Stores Solve?
3. Feature Store Fundamentals, Terminology, and Usage
4. Adding Feature Store to ML Models
5. Model Training and Inference
6. Model to Production and Beyond
7. Feast Alternatives and ML Best Practices
8. Use Case – Customer Churn Prediction

About the Author:

Jayanth Kumar M J is a Lead Data engineer at Cimpress USA. He specializes in building platform components for data scientists and data engineers to make MLops smooth and self-service. He is also a Feast feature store contributor.

Bibliographic Details

Title: Feature Store for Machine Learning: Curate, ...
Publisher: Packt Publishing
Publication Date: 2022
Binding: paperback
Condition: Good