We are in the 4th industrial revolution; companies need to figure out how to survive. In this exciting revolution, machine intelligence has had a more unprecedented impact on business than the internet, and it's the only path to corporate survival in the future. In Data Science for Executives, Nir Kaldero dispels the myths and confusion surrounding this game-changing techn We are in the 4th industrial revolution; companies need to figure out how to survive. In this exciting revolution, machine intelligence has had a more unprecedented impact on business than the internet, and it's the only path to corporate survival in the future. In Data Science for Executives, Nir Kaldero dispels the myths and confusion surrounding this game-changing technology and provides practical strategies for harnessing its profitable power. This essential tome provides illuminating case studies, important guiding principles, and effective on-the-ground actions for incorporating machine intelligence into your organization and employing it to enhance your business though the wealth of data that flows into your business. Leaders don't have to be scientists to unlock the power of AI technology that is already radically altering the industrial landscape. If you're ready to meet the challenges of this new revolution, this essential guide will help you take your business to the next level.
Data Science for Executives: Leveraging Machine Intelligence to Drive Business ROI
We are in the 4th industrial revolution; companies need to figure out how to survive. In this exciting revolution, machine intelligence has had a more unprecedented impact on business than the internet, and it's the only path to corporate survival in the future. In Data Science for Executives, Nir Kaldero dispels the myths and confusion surrounding this game-changing techn We are in the 4th industrial revolution; companies need to figure out how to survive. In this exciting revolution, machine intelligence has had a more unprecedented impact on business than the internet, and it's the only path to corporate survival in the future. In Data Science for Executives, Nir Kaldero dispels the myths and confusion surrounding this game-changing technology and provides practical strategies for harnessing its profitable power. This essential tome provides illuminating case studies, important guiding principles, and effective on-the-ground actions for incorporating machine intelligence into your organization and employing it to enhance your business though the wealth of data that flows into your business. Leaders don't have to be scientists to unlock the power of AI technology that is already radically altering the industrial landscape. If you're ready to meet the challenges of this new revolution, this essential guide will help you take your business to the next level.
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30 review for Data Science for Executives: Leveraging Machine Intelligence to Drive Business ROI
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Rick Echevarria –
An efficient read on data science Mr. Kaldero provides a fair amount of background on the field of data science and follows it up with a comprehensive and practical framework to get any business started down the path of leveraging machine intelligence. The case studies at the end are very helpful in cementing the book’s concepts.
Benjamin Jordan –
Too surface level to be of much use-- but I think I'm the wrong audience. This book is for executives at larger companies that are pivoting into the "digital age". I would have appreciated specifics, not "hire data scientists and then use them." Too surface level to be of much use-- but I think I'm the wrong audience. This book is for executives at larger companies that are pivoting into the "digital age". I would have appreciated specifics, not "hire data scientists and then use them."
Larry Franklin –
Informality I found the book to be a great introduction to machine learning. This would be a great starting point for anyone trying to come up to speed on the big picture.
Nadya Tsech –
Use cases from different industries were especially useful
Juan Camilo Tangarife Palacio –
The framework proposed here seems to be a good start point to implement data science at any company. But I would have preferred that the study cases went a little deeper in technical aspects
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