- Home
- Computers
- Data Processing
- Why Data Science Projects Fail (The Harsh Realities of Implementing AI and Analytics, without the Hype)
Why Data Science Projects Fail (The Harsh Realities of Implementing AI and Analytics, without the Hype)
List Price:
$55.99
- Availability: Confirm prior to ordering
- Branding: minimum 50 pieces (add’l costs below)
- Check Freight Rates (branded products only)
Branding Options (v), Availability & Lead Times
- 1-Color Imprint: $2.00 ea.
- Promo-Page Insert: $2.50 ea. (full-color printed, single-sided page)
- Belly-Band Wrap: $2.50 ea. (full-color printed)
- Set-Up Charge: $45 per decoration
- Availability: Product availability changes daily, so please confirm your quantity is available prior to placing an order.
- Branded Products: allow 10 business days from proof approval for production. Branding options may be limited or unavailable based on product design or cover artwork.
- Unbranded Products: allow 3-5 business days for shipping. All Unbranded items receive FREE ground shipping in the US. Inquire for international shipping.
- RETURNS/CANCELLATIONS: All orders, branded or unbranded, are NON-CANCELLABLE and NON-RETURNABLE once a purchase order has been received.
Product Details
Author:
Douglas Gray, Evan Shellshear
Format:
Paperback
Pages:
222
Publisher:
CRC Press (September 5, 2024)
Language:
English
Audience:
Professional and scholarly
ISBN-13:
9781032660301
Dimensions:
6.125" x 9.1875"
File:
TAYLORFRANCIS-TayFran_260825144931065-20260825.xml
Folder:
TAYLORFRANCIS
List Price:
$55.99
Country of Origin:
United States
Series:
Chapman & Hall/CRC Data Science Series
As low as:
$53.19
Publisher Identifier:
P-CRC
Discount Code:
H
Pub Discount:
30
Weight:
12oz
Case Pack:
40
Imprint:
Chapman and Hall/CRC
Overview
The field of artificial intelligence, data science and analytics is crippling itself. Exaggerated promises of unrealistic technologies, simplifications of complex projects and marketing hype are leading to an erosion of trust in one of our most critical approaches to making decisions: data driven.
