Building Machine Learning Systems with a Feature Store, 9781098165239
Paperback
Unlock ML systems: Data, pipelines, and the power of feature stores.
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Building Machine Learning Systems with a Feature Store

batch, real-time, and llm systems

$162.10

  • Paperback

    450 pages

  • Release Date

    30 November 2025

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Summary

Mastering Machine Learning Systems with Feature Stores

Get up to speed on a new unified approach to building machine learning (ML) systems with batch data, real-time data, and large language models (LLMs) based on independent, modular ML pipelines and a shared data layer. With this practical book, data scientists and ML engineers will learn in detail how to develop, maintain, and operate modular ML systems.

Author Jim Dowling introduces fundamental MLOps principles and pract…

Book Details

ISBN-13:9781098165239
ISBN-10:1098165233
Author:Jim Dowling
Publisher:O'Reilly Media
Imprint:O'Reilly Media
Format:Paperback
Number of Pages:450
Release Date:30 November 2025
Weight:0g
Dimensions:232mm x 178mm
About The Author

Jim Dowling

Jim Dowling is CEO of Hopsworks and an Associate Professor at KTH Royal Institute of Technology. He’s led the development of Hopsworks that includes the first open-source feature store for machine learning. He has a unique background in the intersection of data and AI. For data, he worked at MySQL and later led the development of HopsFS, a distributed file system that won the IEEE Scale Prize in 2017. For AI, his PhD introduced Collaborative Reinforcement Learning, and he developed and taught the first course on Deep Learning in Sweden in 2016. He also released a popular online course on serverless machine learning using Python. This combined background of Data and AI helped him realize the vision of a feature store for machine learning based on general purpose programming languages, rather than the earlier feature store work at Uber on DSLs. He was the first evangelist for feature stores, helping to create the feature store product category through talks at industry conferences, like Data/AI Summit, PyData, OSDC, and educational articles on feature stores. He is the organizer of the annual feature store summit conference and the featurestore.org community, as well as co-organizer of PyData Stockholm.

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