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Author:   J. Mark Bishop ,  Gabriel Seiberth
Publisher:   Taylor & Francis Ltd
Imprint:   Routledge
Weight:   0.650kg
ISBN:  

9781032911229

ISBN 10:   1032911220
Pages:   238
Publication Date:   23 December 2025
Audience:   College/higher education ,  Professional and scholarly ,  Professional and scholarly ,  Tertiary & Higher Education ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand  
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Table of Contents

Foreword. Preface. About the Authors. Chapter 1 Self Driving to the Future. Chapter 2 Computing Machinery & Intelligence. Chapter 3 First Steps in Computer Vision. Chapter 4 The Tortoise and the Hare. Chapter 5 The DARPA Grand Challenges. Chapter 6 Forms of Machine Learning. Chapter 7 Types of ML models. Chapter 8 Second & Third DARPA Challenges. Chapter 9 Theory, Empiricism, and Data. Chapter 10 New Forms of Learning. Chapter 11 New Types of Model. Chapter 12 A Whole New Industry Unfolding. Chapter 13 Recurrent Sequence‑To‑Sequence Learning. Chapter 14 Attention Is All You Need. Chapter 15 LLMs and Multi‑Modal Systems. Chapter 16 End‑to‑end Neural Networks. Chapter 17 A Question of Strategy. Chapter 18 Green Lights Ahead!. Bibliography. Index

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Author Information

J. Mark Bishop has served as Professor of Cognitive Computing and Director of The Centre for AI and Analytics (TCIDA), at Goldsmiths, University of London. Mark was elected Chair of the AISB (the UK professional body for AI, and the oldest such organisation in the world) from 2010-2014. He currently acts as Chief Scientific Advisor to Fact3602 and is an International Fellow of the Karel Čapek Center, Praha, Czech Republic. Gabriel Seiberth is a distinguished automotive industry professional with 25 years of experience in management consulting and technology. He currently holds a top management position at a leading global electronics and services company for the automotive industry. Previously, he served as Managing Director at a leading global technology and consulting firm, where he authored several influential thought leadership pieces around autonomous driving.

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