Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
How Generative AI Helps Predictive AI
 Originally published in Forbes, August 21, 2024 This is the...
4 Ways Machine Learning Can Perpetuate Injustice and What to Do About It
 Originally published in Built In, July 12, 2024 When ML...
The Great AI Myth: These 3 Misconceptions Fuel It
 Originally published in Forbes, July 29, 2024 The hottest thing...
Where FICO Gets Its Data for Screening Two-Thirds of All Card Transactions
 Originally published in The European Business Review, March 21,...

Original Content

A University Curriculum Supplement to Teach a Business Framework for ML Deployment

    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

The AI Playbook: Providing Important Reminders to Data Professionals

 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...

Decode the Algorithm: Navigate the World of Machine Learning in Business with ‘The AI ​​Playbook’

  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...

To Deploy Machine Learning, You Must Manage Operational Change—Here Is How UPS Got It Right

 Originally published in Harvard Data Science Review. For 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...

Cracking the Business Code of Clusters

 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...

The Key to ML Success: A Book Review of “The AI Playbook”

  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...

The Problem with AI Hype and the True Value of ML

  Eric Siegel, was interviewed on the Digital Communicators podcast about his 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...

BizML: Bridging the Gap Between Data Science and Business

  Eric Siegel, author of The AI Playbook, was interviewed by Pragmatic Data about a business paradigm to get machine learning deployed, bizML.  Click here to listen to the podcast episode.  “There’s a gap between the technical...

The AI Hype Cycle Is Distracting Companies

 Originally published in Harvard Business Review. Machine learning has an “AI” problem. With new breathtaking capabilities from generative AI released every several months — and AI hype escalating at an even higher rate — it’s high time...

HR Analytics: Measuring Acquisition, Retention & Satisfaction

 Your firm is growing rapidly, and to maintain pace, talent acquisition managers are searching for innovative approaches to attract, keep and satisfy qualified candidates. You see, less qualified applicants are creeping in, employee turnover is as high...

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