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About This Book
This book teaches you 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
You can learn more by watching our free webinar
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.
Part 1: Approaching an Intelligent Systems Project
This part sets the groundwork for a successful Intelligent Systems project. It describes what Intelligent Systems are, and what they are good for. It refreshes some important background. It explains how to ensure an Intelligent System has a useful, achievable goal. And it gives an overview of what to expect when taking on an Intelligent Systems project.
Chapter 1: Introducing Intelligent Systems
Chapter 2: Knowing When to Use Intelligent Systems
Chapter 3: A Brief Refresher on Working With Data
Chapter 4: Defining the Intelligent System's Goals
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.
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