eBook

Reactive Machine Learning Systems

Jeff Smith, Software Engineer, data Artisans

Audience: Architects, Managers

Technical level: Introductory

Reactive Machine Learning Systems teaches you how to implement reactive design solutions in your machine learning systems to make them as reliable as a well-built web app. This example-rich guide starts with an overview of machine learning systems while focusing on where reactive design fits. Then you’ll discover how to develop design patterns to implement and coordinate ML subsystems. Using Scala and powerful frameworks such as Spark, MLlib, and Akka, you’ll learn to quickly and reliably move from a single machine to a massive cluster. Finally, you’ll see how you can operate a large-scale machine learning system over time. By the end, you’ll be employing the principles of reactive systems design to build machine learning applications that are responsive, resilient, and elastic.

The free sample PDF available here includes chapter 1. All registrants qualify for a Lightbend discount and will save 40% off the price of Reactive Machine Learning Systems (all formats) as it becomes available by referencing promotional code lbsmith. If you are interested in purchasing the full book get it here. Offer only valid at manning.com.

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ABOUT AUTHOR(S)

Jeff Smith, Software Engineer, data Artisans

About Lightbend

Lightbend (Twitter: @Lightbend) provides the leading Reactive application development platform for building distributed systems. Based on a message-driven runtime, these distributed systems, which include microservices and streaming fast data applications, can effortlessly scale on multi-core and cloud architectures. Many of the most admired brands around the globe are transforming their businesses with our platform, engaging billions of users every day through software that is changing the world. For more information on Lightbend, visit: lightbend.com