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Why AI/Data Science Projects Fail [Hardback]

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Why AI/Data Science Projects FailPalielināt
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Permanent link: https://www.kriso.lv/db/9781636390406.html
Recent data shows that 87% of Artificial Intelligence/Big Data projects don’t make it into production (VB Staff, 2019), meaning that most projects are never deployed. This book addresses five common pitfalls that prevent projects from reaching deployment and provides tools and methods to avoid those pitfalls. Along the way, stories from actual experience in building and deploying data science projects are shared to illustrate the methods and tools. While the book is primarily for data science practitioners, information for managers of data science practitioners is included in the Tips for Managers sections.
Preface
Introduction and Background
Project Phases and Common Project Pitfalls
Define Phase
Making the Business Case: Assigning Value to Your Project
Acquisition and Exploration of Data Phase
Model-Building Phase
Interpret and Communicate Phase
Deployment Phase
Summary of the five Methods to Avoid Common Pitfalls
References
Author Biography