Feature Store for Machine Learning

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

Key Features

• Understand the significance of the feature store in the ML lifecycle
• Discover how features can be shared, discovered and re-used
• Learn to make features available for online models during inference

Book Description

Feature store is one of the storage layers in Machine Learning operations, where data scientists and ML engineers can store transformed/curated features for ML models. This makes them available for model training, inference (batch and online), and reuse in other ML pipelines. Knowing how to utilize feature stores to their fullest potential can save you a lot of time and effort, and this book will teach you everything you need to know to do so.

With Feature Store for Machine Learning, data scientists will learn how to utilize feature stores to share and reuse each other's work and expertise. They'll be able to implement practices which will help in eliminating reprocessing of data, providing model reproducible capabilities and reducing duplication work, thus improving time to production of the machine learning model.

While this machine learning 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. The book provides a hands-on approach to implementation and associated methodologies that will have you up-and-running and productive in no time.

By the end of this book, you will understand the need for feature stores and how to use them in your ML projects, both on your local system or on the cloud.

What you will learn

• Understand why we need Feature Stores and where they are currently implemented
• Sort, reproduce, and share features with others through Feature Stores
• Explore the different components and capabilities of a feature store
• Learn how to use feature stores to build your features repository in ML lifecycle
• Accelerate your model lifecycle and reduce costs
• Deploy your first Feature Store for production use cases

Who This Book Is For

If you have a solid grasp on ML basics, but need a comprehensive overview of features stores to gain confidence using them, then this book is for you.

Data/ML engineers and Data scientists who build Machine Learning models for production systems in any domain, those supporting data engineers in productionizing ML models, and Platform engineers who build data science(ML) platforms for the organization will also find plenty of practical advice in the later chapters of this book.

Table of Contents

1. Overview of ML life cycle
2. What does feature store solve
3. Overview of Feature store, Definitions and terminologies.
4. Add feature store to ML
5. Model Training and Inference
6. Model to production and beyond
7. Overview of Feature stores in market, Best practices
8. Use case 1: Customer churn