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"I would consider it a must read for any engineers or managers looking to use ML in their solutions."

-Amazon review

"I would consider it a must read for any engineers or managers looking to use ML in their solutions."

-Amazon review

About This Book

Learn how to build an Intelligent System from beginning to end and leverage machine learning in practice, including:

  • Understand Intelligent Systems: What they are, what they are good for, and how to set one up for success
  • Design an intelligent user experience: Achieve your goals and produce data to make the Intelligent System better over time
  • Implement an Intelligent System: Execute, manage, and measure Intelligent Systems in practice
  • Create intelligence: Reliably use a variety of approaches, including machine learning
  • Orchestrate an Intelligent System: Bring the parts together throughout its life cycle to achieve the impact you want

"This book explains ... with lots of concrete examples and very clear explanations about each and every step required to deliver a successful intelligent experience. ... I also really liked the tone of the book, full of funny examples and witty remarks."

-Amazon review

This Book is For

Anyone involved in building software who wants to take part in the AI revolution:

Machine Learning Practitioners who want to know how to build models that work in an end-to-end system and create impact.

Software Engineers who want to learn how use their existing skills to contribute to building Intelligent Systems.

Technical Managers and Program Managers who want to leverage machine learning and need to know how to get started and make good decisions along the way.

And Students who want to benefit from a decade of experience in applying machine learning to practical problems.

"It explains intelligent system in very practical manner applying knowledge from years of experience. You can avoid a lot of pitfalls just by reading this book."

-Amazon review

About the Author

Geoff Hulten is a Machine Learning Scientist with a PhD in machine learning.

He has managed applied machine learning teams for over a decade, building dozens of Internet scale Intelligent Systems that have hundreds of millions of interactions with users every day.

His research has appeared in top international conferences, received thousands of citations, and won a SIGKDD Test of Time award for influential contributions to the data mining research community that have stood the test of time.

"The author goes way beyond the theories and models to help simplify the complexities in building, measuring and managing complete large scale intelligence systems."

-Amazon Review