Buch, Englisch, 65 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 169 g
How to Avoid Project Pitfalls
Buch, Englisch, 65 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 169 g
Reihe: Synthesis Lectures on Computation and Analytics
ISBN: 978-3-031-00557-2
Verlag: Springer International Publishing
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.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
- Wirtschaftswissenschaften Betriebswirtschaft Management Entscheidungsfindung
- Mathematik | Informatik Mathematik Stochastik
- Mathematik | Informatik EDV | Informatik Business Application Mathematische & Statistische Software
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Optimierung
Weitere Infos & Material
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.