Description
Part 1: Approaching an Intelligent System 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.-
Part 2: Intelligent Experiences.-
Chapter 5: The Components of Intelligent Experiences.-
Chapter 6: Why Creating Intelligence Experiences Is Hard.-
Chapter 7: Balancing Intelligent Experiences.-
Chapter 8: Modes of Intelligent Interaction.-
Chapter 9: Getting Data from Experience.-
Chapter 10: Verifying Intelligent Experiences.-
Part 3: Implementing Intelligence.-
Chapter 11: The Components of an Intelligence Implementation.-
Chapter 12: The Intelligence Runtime.-
Chapter 13: Where Intelligence Lives.-
Chapter 14: Intelligence Management.-
Chapter 15: Intelligent Telemetry.-
Part 4: Creating Intelligence.-
Chapter 16: Overview of Intelligence.-
Chapter 17: Representing Intelligence.-
Chapter 18: The Intelligence Creation Process.-
Chapter 19: Evaluating Intelligence.-
Chapter 20: Machine Learning Intelligence.-
Chapter 21: Organizing Intelligence.-
Part 5: Orchestrating Intelligent Systems.-
Chapter 22: Overview of Intelligence Orchestration.-
Chapter 23: The Intelligence Orchestration Environment.-Chapter 24: Dealing with Mistakes.-
Chapter 25: Adversaries and Abuse.-
Chapter 26: Approaching Your Own Intelligent System.-
Author: Geoff Hulten
Publisher: Apress
Published: 03/07/2018
Pages: 339
Binding Type: Paperback
Weight: 1.40lbs
Size: 10.00h x 7.00w x 0.76d
ISBN13: 9781484234310
ISBN10: 1484234316
BISAC Categories:
- Computers | Computer Science
- Computers | Database Administration & Management
- Computers | Data Science | General
About the Author
Geoff Hulten is a Machine Learning Scientist and 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.