AIQ - How artificial intelligence works and how we can harness its power for a better world

Name: AIQ
Price: 9.49 EUR
Author: Nick Polson
ISBN: 9781473554368

Edition en anglais

Nick Polson, James Scott

Transworld Digital
Paru le : 07/06/2018

____________________What is AIQ? How does it work? Most importantly, how can it help us? Two leading data scientists offer an up-close and user-friendly... > Lire la suite

9,49 €

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____________________What is AIQ? How does it work? Most importantly, how can it help us? Two leading data scientists offer an up-close and user-friendly look at artificial intelligence and how to harness its power for a better world. 'A positive and entertaining look at the great potential unlocked by marrying human creativity with powerful machines.' Steven D. Levitt, co-author of Freakonomics____________________Dozens of times per day, we all interact with intelligent machines that are constantly learning from the wealth of data now available to them.
These machines, from smart phones to talking robots to self-driving cars, are remaking the world in the twenty first century in the same way that the Industrial Revolution remade the world in the nineteenth. AIQ is based on a simple premise: if you want to understand the modern world, then you have to know a little bit of the mathematical language spoken by intelligent machines. AIQ will teach you that language but in an unconventional way, anchored in stories rather than equations.

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Date de parution : 07/06/2018
Editeur : Transworld Digital
ISBN : 978-1-4735-5436-8
EAN : 9781473554368
Format : ePub

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Nick Polson is Professor of Econometrics and Statistics at the Chicago Booth School of Business. Nick is a Bayesian statistician involved in research in machine intelligence, deep learning, and computational methods for Bayesian inference. He has developed a number of new algorithms and applied them across a variety of fields, including finance, economics, transportation and applied statistics. Nick was born in England, studied maths at Worcester College, Oxford; and obtained a PhD in Bayesian Statistics.
He regularly speaks to large audiences in the US, UK and the rest of Europe. James Scott is Associate Professor of Statistics at the University of Texas at Austin. James is a statistician and data scientist who studies Bayesian inference and computational methods for big data. His has collaborated with scientists in a wide variety of fields, including health care, nuclear security, linguistics, political science, finance, management, infectious disease, astronomy, neuroscience, transportation and molecular biology.
He has also worked with clients across many different industries, from tech startups to large multinational firms. James lives in Austin, Texas with his wife, Abigail. His academic research has been featured in The New York Times, the Washington Post, ABC, NBC, Fox, the BBC UK, BBC World News, Radio 4, The Guardian and many other prominent media outlets.