Machine Learning Times » Predictive Analytics
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Machine Learning Times » Predictive Analytics
1w ago
Originally published in Forbes, April 10, 2024 When OpenAI’s board momentarily ousted Sam Altman from his post as CEO last November, the media obsession was… intense. Why so much fuss about a corporate drama? The public mania—and perhaps the ousting itself—came in no small part from a widespread belief that the company is well on ..read more
Machine Learning Times » Predictive Analytics
2w ago
Originally published in Harvard Business Review Machine learning might be the world’s most important general-purpose technology, but it’s notoriously difficult to launch. Outside of Big Tech and a handful of other leading companies, machine learning initiatives routinely fail to deploy, never realizing value. What’s missing? A specialized business practice suitable for wide adoption. This article ..read more
Machine Learning Times » Predictive Analytics
2w ago
Listen to Eric Siegel, former Columbia University Professor, discuss his book The AI Playbook: Mastering the Rare Art of Machine Learning Deployment. Radio show: Bloomberg Businessweek Hosts: Carol Massar and Tim Stenovec. Producer: Paul Brennan. Click here to listen to the full 10-minute segment Transcript: 00:00 Speaker 1 This is Bloomberg Business Week with ..read more
Machine Learning Times » Predictive Analytics
1M ago
This article from Morgan Vawter, Global Vice President of Data & Analytics at Unilever, serves as the foreword to The AI Playbook: Mastering the Rare Art of Machine Learning Deployment, by Eric Siegel. Morgan will present a keynote at Machine Learning Week, June 4-7, 2024 in Phoenix, AZ – where registrants will receive ..read more
Machine Learning Times » Predictive Analytics
1M ago
No question about it: We, as consumers have our favorites, and as a marketer, you would certainly hope that your establishment will be top of mind when shopping decisions are being made. The fact is that while a consumer might enjoy transacting with you, if they like your competitor somewhat more, you may be in ..read more
Machine Learning Times » Predictive Analytics
2M ago
Originally published in Fast Company, Jan 5, 2024. Eric Siegel had already been working in the machine learning world for more than 30 years by the time the rest of the world caught up with him. Siegel’s been a machine learning (ML) consultant to Fortune 500 companies, an author, and a former former Columbia University professor ..read more
Machine Learning Times » Predictive Analytics
3M ago
In 2023, as a visiting analytics professor at UVA Darden School of Business, I developed and “field tested” a curriculum supplement designed to augment introductory data science courses so that they cover the business-side execution of machine learning projects – the know-how needed to ensure successful deployment. In this article, I motivate and ..read more
Machine Learning Times » Predictive Analytics
3M ago
Originally published in DATAVERSITY. This article reviews the new book, The AI Playbook, by my colleague here at The Machine Learning Times, Executive Editor Eric Siegel. Free book: Come to Machine Learning Week – June 4-7, 2024 in Phoenix, AZ – to meet author Eric Siegel, the event founder, and receive a complimentary copy. –Luba Gloukhova, Editor-in-Chief Eric Siegel’s “The ..read more
Machine Learning Times » Predictive Analytics
4M ago
Originally published in Harvard Data Science Review. For much more about the trials and tribulations UPS overcame on its road to success, see Eric Siegel’s new book, The AI Playbook. Free book: Come to Machine Learning Week – June 4-7, 2024, in Phoenix, AZ – to meet author Eric Siegel, the event founder, and receive a ..read more
Machine Learning Times » Predictive Analytics
4M ago
Winning with Data Science is a compelling and comprehensive guide for customers of data science. It teaches readers how to work with data scientists by emphasizing real-world business applications and focusing on how to collaborate productively with data science teams. The book takes a narrative approach with fictitious characters embracing new projects involving data science ..read more