Artificial Intelligence: Evolution and Revolution

by Steven Astorino, Dr. Jean-François Puget, Mark Simmonds

Overview

Unlock the Power of AI: A Comprehensive Guide to Evolution and Revolution

Navigate the rapidly evolving world of Artificial Intelligence with this insightful guide. From the foundational concepts of machine learning and deep learning to the ethical considerations and future trends, this book provides a comprehensive overview of AI's transformative potential.

Discover how AI is being applied across diverse industries, from healthcare to finance, and gain practical knowledge of key algorithms and implementation strategies. Address the challenges of AI bias and ensure transparency with explainable AI techniques. Prepare for the future by understanding the AI Ladder and its role in accelerating your AI journey. This book is for data scientists, business professionals, and anyone eager to harness the power of AI.

Product Details

ISBN-13:	9781583478936
Publisher:	MC Press, LLC
Publication date:	10/01/2019
Sold by:	INDEPENDENT PUB GROUP - EPUB - EBKS
Format:	eBook
Pages:	120
File size:	2 MB

About the Author

Steven Astorino is Vice President of Development, Data and AI and Canada Lab Director at IBM. He is a development executive with proven transformational leadership and expertise in leading large enterprise development. He has been leading and driving the machine learning and data science strategy for IBM's analytics group. Steve has a Bachelor's Degree in Computer Science. Dr. Jean-François Puget is the technical executive for all IBM machine learning offerings. He holds a PhD in Machine Learning, has published over 70 scientific papers, and practices machine learning competitions as a Kaggle Grandmaster under the name CPMP. Mark Simmonds is a Program Director in IBM Data and AI communications. He writes extensively on machine learning and data science, holding a number of author recognition awards. He previously worked as an IT architect leading complex infrastructure design projects. He is a member of the British Computer Society and hold a Bachelor's Degree in Computer Science.

Table of Contents

Chapter 1: Machine Learning—The Early Years Chapter 2: Industry Adoption of AI Chapter 3: Bias and Explainability Chapter 4: Ethically Speaking Chapter 5: Theory vs. Reality (10 Lessons from the Field) Chapter 6: From Machine Learning to Learning Machines Chapter 7: 10 Machine-Learning Methods That Every Data Scientist Should Know Chapter 8: Machine Learning for the Masses Chapter 9: Operationalizing ML/AI into Your Business Processes Chapter 10: Five, Ten, Fifty Chapter 11: Conclusion