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Artificial Intelligence
Artificial Intelligence

Artificial Intelligence

Evolution and Revolution

COMPUTERS

120 Pages, 6 x 9

Formats: PDF, EPUB, Mobipocket

PDF, $16.95 (US $16.95) (CA $22.95)

Publication Date: October 2019

ISBN 9781583478950

Rights: WOR X AU & NZ

MC Press (Oct 2019)

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Overview

Throughout history, machines have been introduced to society to help automate tasks, improve productivity, and reduce costs. And, in just a few years, computers have evolved from centralized, number-crunching monoliths to separate, miniaturized systems that can be found in billions of interconnected items such as cellphones, wearable devices, automobiles, home appliances, and more.From humble evolutions in research papers and labs, artificial intelligence (AI)—which encompasses Machine Learning (ML) and Deep Learning (DL)—has matured in its many forms, infused in applications that can learn on their own and become progressively smarter with each interaction and transaction. Coupled with immense stores of data, maturity in CPU and GPU hardware, the invention of new, open source deep learning algorithms, and cloud technologies, operational AI has become available to the masses, setting the wheels in motion for a worldwide AI revolution that has never been seen before.This book attempts to help the reader on their AI journey by covering the concepts of AI, Machine Learning, and Deep Learning in its many forms; key ML and DL algorithms data scientists should learn; ethical challenges for the use of AI; how AI is being used across industries; possible future outlook for AI, and an AI Ladder to help accelerate the AI journey.

Author Biography

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.