Product details:
| ISBN13: | 9781789665413 |
| ISBN10: | 1789665418 |
| Binding: | Hardback |
| No. of pages: | 264 pages |
| Size: | 240x164x25 mm |
| Weight: | 640 g |
| Language: | English |
| 251 |
Category:
Driving Digital Transformation through Data and AI
A Practical Guide to Delivering Data Science and Machine Learning Products
Edition number: 1
Publisher: Kogan Page
Date of Publication: 3 November 2020
Normal price:
Publisher's listprice:
GBP 97.00
GBP 97.00
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42 166 (40 158 HUF + 5% VAT )
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Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
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Short description:
Avoid being left behind and make data science and artificial intelligence a profitable part of your business with this practical guide to product delivery.
Long description:
Leading tech companies such as Netflix, Amazon and Uber use data science and machine learning at scale in their core business processes, whereas most traditional companies struggle to expand their machine learning projects beyond a small pilot scope. This book enables organizations to truly embrace the benefits of digital transformation by anchoring data and AI products at the core of their business.
It provides executives with the essential tools and concepts to establish a data and AI portfolio strategy as well as the organizational setup and agile processes that are required to deliver machine learning products at scale. Key consideration is given to advancing the data architecture and governance, balancing stakeholder needs and breaking organizational silos through new ways of working.
Each chapter includes templates, common pitfalls and global case studies covering industries such as insurance, fashion, consumer goods, finance, manufacturing and automotive. Covering a holistic perspective on strategy, technology, product and company culture, Driving Digital Transformation through Data and AI guides the organizational transformation required to get ahead in the age of AI.
It provides executives with the essential tools and concepts to establish a data and AI portfolio strategy as well as the organizational setup and agile processes that are required to deliver machine learning products at scale. Key consideration is given to advancing the data architecture and governance, balancing stakeholder needs and breaking organizational silos through new ways of working.
Each chapter includes templates, common pitfalls and global case studies covering industries such as insurance, fashion, consumer goods, finance, manufacturing and automotive. Covering a holistic perspective on strategy, technology, product and company culture, Driving Digital Transformation through Data and AI guides the organizational transformation required to get ahead in the age of AI.
