Stock photo: cover may vary
Why Data Science Projects Fail: The Harsh Realities of Implementing Ai and Analytics, Without the Hype Hardback - 2024
by Gray, Douglas/ Shellsear, Evan
- New
- Hardback
A$362.44
A$29.23
Delivery to USA
Standard delivery: 7 to 14 days
More delivery options
Standard delivery: 7 to 14 days
Ships from Revaluation Books (Devon, United Kingdom)
Details
- Title Why Data Science Projects Fail: The Harsh Realities of Implementing Ai and Analytics, Without the Hype
- Author Gray, Douglas/ Shellsear, Evan
- Binding Hardback
- Condition New
- Pages 208
- Volumes 1
- Language ENG
- Publisher Chapman & Hall
- Publication date 2024
- Illustrated Yes
- Features Bibliography, Illustrated, Index
- Bookseller's Inventory # x-103266133X
- ISBN 9781032661339 / 103266133X
- Weight 1.08 lbs (0.49 kg)
- Dimensions 9.21 x 6.14 x 0.56 in (23.39 x 15.60 x 1.42 cm)
- Category Computers - General Information
- Library of Congress subjects Artificial intelligence, Decision making - Mathematical models
- Library of Congress Catalogue Number 2024015369
- Dewey Decimal Code 001.420
- Quantity available 2
About Revaluation Books Devon, United Kingdom
Biblio member since 2020
General bookseller of both fiction and non-fiction.
Reader reviews for Why Data Science Projects Fail: The Harsh Realities of Implementing Ai and Analytics, Without the Hype
Write a review for this book
Important Terms and Guidelines
- Please focus on the book’s content and context. Also, add any personal comments as to how you enjoyed the book. Substantiate your likes and dislikes. You may make comparisons to other books.
- Reviews must be at least 140 characters in length.
- Please do not reveal critical plot elements.
- This is not a help line. Contact customer support if you need help.
Your review must not include:
- Obscenities, discriminatory language, or other insulting language not suitable for public domain
- Advertisements, “spam” content, or references to other products, offers or websites.
- Email addresses, URLs, phone numbers, physical addresses or other contact information.
- Overly critical comments about other reviews or reviewers
- Time-sensitive material (i.e. promotional tours, seminars, lectures, etc.)
- Availability, price, or alternative ordering/shipping information
