Cardinal

Why Data Science Projects Fail: The Harsh Realities of Implementing AI and

Description: 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. This book aims to fix this by countering the AI hype with a dose of realism. Written by two experts in the field, the authors firmly believe in the power of mathematics, computing, and analytics, but if false expectations are set and practitioners and leaders don’t fully understand everything that really goes into data science projects, then a stunning 80% (or more) of analytics projects will continue to fail, costing enterprises and society hundreds of billions of dollars, and leading to non-experts abandoning one of the most important data-driven decision-making capabilities altogether. For the first time, business leaders, practitioners, students, and interested laypeople will learn what really makes a data science project successful. By illustrating with many personal stories, the authors reveal the harsh realities of implementing AI and analytics.

Price: 27.34 USD

Location: Matraville, NSW

End Time: 2024-11-28T23:27:34.000Z

Shipping Cost: 0 USD

Product Images

Why Data Science Projects Fail: The Harsh Realities of Implementing AI andWhy Data Science Projects Fail: The Harsh Realities of Implementing AI and

Item Specifics

Restocking Fee: No

Return shipping will be paid by: Buyer

All returns accepted: Returns Accepted

Item must be returned within: 60 Days

Refund will be given as: Money Back

EAN: 9781032660301

UPC: 9781032660301

ISBN: 9781032660301

MPN: N/A

Item Height: 1.2 cm

Item Weight: 0.31 kg

Number of Pages: 210 Pages

Language: English

Publication Name: Why Data Science Projects Fail : The Harsh Realities of Implementing AI and Analytics, Without the Hype

Publisher: CRC Press LLC

Publication Year: 2024

Subject: Enterprise Applications / Business Intelligence Tools, Intelligence (Ai) & Semantics, Computer Science, General

Type: Textbook

Author: Douglas Gray, Evan Shellshear

Subject Area: Mathematics, Computers

Item Length: 9.2 in

Item Width: 6.1 in

Series: Chapman and Hall/Crc Data Science Ser.

Format: Trade Paperback

Recommended

How to Resist Amazon and Why: The Fight for Local Economics, Data Privacy, F...
How to Resist Amazon and Why: The Fight for Local Economics, Data Privacy, F...

$4.71

View Details
Dark Data: Why What You Dont Know Matters - Paperback - GOOD
Dark Data: Why What You Dont Know Matters - Paperback - GOOD

$13.97

View Details
Womens Quick Facts: Compelling Data on Why Women Matter - Paperback - VERY GOOD
Womens Quick Facts: Compelling Data on Why Women Matter - Paperback - VERY GOOD

$4.57

View Details
Breached!: Why Data Security Law Fails and How to Improve It (Hardback or Cased
Breached!: Why Data Security Law Fails and How to Improve It (Hardback or Cased

$25.62

View Details
Big Data Big Design: Why Designers Should Care about Artificial Intelligence
Big Data Big Design: Why Designers Should Care about Artificial Intelligence

$8.60

View Details
Why Data Science Projects Fail: The Harsh Realities of Implementing AI and Analy
Why Data Science Projects Fail: The Harsh Realities of Implementing AI and Analy

$174.55

View Details
Why Information Grows : The Evolution of Order, from Atoms to Economies...
Why Information Grows : The Evolution of Order, from Atoms to Economies...

$21.00

View Details
Why Information Grows : The Evolution of Order, from Atoms to Eco
Why Information Grows : The Evolution of Order, from Atoms to Eco

$8.46

View Details
The Talent Delusion : Why Data, Not Intuition, Is the Key to Unlo
The Talent Delusion : Why Data, Not Intuition, Is the Key to Unlo

$8.46

View Details
Measuring Race: Why Disaggregating Data Matters for Addressing Educational Inequ
Measuring Race: Why Disaggregating Data Matters for Addressing Educational Inequ

$33.17

View Details