Why AI/Data Science Projects Fail

Joyce Weiner (Autor)

Buch | Softcover

77 Seiten

2020
Morgan & Claypool Publishers (Verlag)
978-1-63639-038-3 (ISBN)

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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.

Joyce Weiner is a Principal Engineer at Intel Corporation. Her area of technical expertise is data science and using data to drive efficiency. Joyce is a black belt in Lean Six Sigma. She has a B.S. in Physics from Rensselaer Polytechnic Institute, and an M.S. in Optical Sciences from the University of Arizona. She lives with her husband outside Phoenix, Arizona.

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

Erscheinungsdatum	18.01.2021
Reihe/Serie	Synthesis Lectures on Computation and Analytics
Verlagsort	San Rafael
Sprache	englisch
Maße	191 x 235 mm
Themenwelt	Mathematik / Informatik ► Informatik ► Datenbanken
	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Wirtschaft ► Betriebswirtschaft / Management ► Projektmanagement
ISBN-10	1-63639-038-2 / 1636390382
ISBN-13	978-1-63639-038-3 / 9781636390383
Zustand	Neuware