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Titlebook: Building Intelligent Systems; A Guide to Machine L Geoff Hulten Book 2018 Geoff Hulten 2018 Machine Learning.Machine Learning Engineering.

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發(fā)表于 2025-3-21 17:41:45 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Building Intelligent Systems
期刊簡(jiǎn)稱A Guide to Machine L
影響因子2023Geoff Hulten
視頻videohttp://file.papertrans.cn/192/191679/191679.mp4
發(fā)行地址Shows you how to plan for the various phases of an intelligent system from implementation to operation—what is required to succeed, and when it is time to progress.Teaches you how to craft experiences
圖書封面Titlebook: Building Intelligent Systems; A Guide to Machine L Geoff Hulten Book 2018  Geoff Hulten 2018 Machine Learning.Machine Learning Engineering.
影響因子Produce a fully functioning Intelligent System that leverages machine learning and data from user interactions to improve over time and achieve success..This book teaches you how to build an Intelligent System from end to end and leverage machine learning in practice. You will understand how to apply your existing skills in software engineering, data science, machine learning, management, and program management to produce working systems..Building Intelligent Systems. is based on more than a decade of experience building Internet-scale Intelligent Systems that have hundreds of millions of user interactions per day in some of the largest and most important software systems in the world....What You’ll Learn..Understand the concept of an Intelligent System:. What it is good for, when you need one, and how to set it up for success.Design an intelligent user experience:. Produce data to help make the Intelligent System better over time.Implement an Intelligent System:. Execute, manage, and measure Intelligent Systems in practice.Create intelligence:. Use different approaches, including machine learning.Orchestrate an Intelligent System:. Bring the parts together throughout its life cycl
Pindex Book 2018
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Getting Data from Experiencehe intelligence they can create is much greater. An ideal intelligent experience will control the interactions between users and the Intelligent System so that the record of those interactions makes it easy to create high-quality intelligence.
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發(fā)表于 2025-3-22 07:39:36 | 只看該作者
Intelligence Managementg monitored over time. Intelligence management bridges the gap between intelligence creation (which is discussed in Part 4 of this book) and intelligence orchestration (which is discussed in Part 5), by making it safer and easier to deploy new intelligence and enable it for users.
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Getting Data from Experiencehe intelligence they can create is much greater. An ideal intelligent experience will control the interactions between users and the Intelligent System so that the record of those interactions makes it easy to create high-quality intelligence.
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發(fā)表于 2025-3-22 22:28:12 | 只看該作者
Intelligence Managementg monitored over time. Intelligence management bridges the gap between intelligence creation (which is discussed in Part 4 of this book) and intelligence orchestration (which is discussed in Part 5), by making it safer and easier to deploy new intelligence and enable it for users.
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