Machine Learning Times
EXCLUSIVE HIGHLIGHTS
2 More Ways To Hybridize Predictive AI And Generative AI
  Originally published in Forbes Predictive AI and generative AI...
How To Overcome Predictive AI’s Everyday Failure
  Originally published in Forbes Executives know the importance of predictive...
Our Last Hope Before The AI Bubble Detonates: Taming LLMs
  Originally published in Forbes To know that we’re in...
The Agentic AI Hype Cycle Is Out Of Control — Yet Widely Normalized
  Originally published in Forbes I recently wrote about how...

Author Archive

Whole Foods is Reportedly Using a Heat Map to Track Stores at Risk of Unionization

 Originally published in The Verge, April 20, 2020 The heat map apparently uses more than two dozen different metrics to track which Whole Foods stores may unionize. The heat map focuses on monitoring three main areas: “external risks,” “store risks,” and “team member sentiment,” according to Business Insider. Here are some examples of “external risks,”

Industrial Asset Optimization: Connecting Machines Directly with Data Scientists

 For more from this author, attend his virtual presentation, Industrial Asset Optimization:  Machine-to-Cloud/Edge Analytics, at Predictive Analytics World for Industry 4.0, May 31-June 4, 2020.  For industrial firms to realize the benefits promised by embracing Industry 4.0,...

Data Science Strategies for Banks and Credit Unions During COVID-19 and Beyond

 For more information on this topic, attend the virtual conference, Predictive Analytics World for Industry 4.0, May 31-June 4, 2020.  So many things are changing rapidly as the world responds to the risk from coronavirus. We know...

4 Steps to Ensure Your AI/Machine Learning System Survives COVID-19

 Originally published in KDNuggets, April, 2020. Many AI models rely on historical data to make predictions on future behavior. So, what happens when consumer behavior across the planet makes a 180 degree flip? Companies are quickly seeing...

AI is an Ideology, Not a Technology

 Originally published in Wired.com, March 15, 2020. At its core, “artificial intelligence” is a perilous belief that fails to recognize the agency of humans. A leading anxiety in both the technology and foreign policy worlds today is...

“If We Place Graduates Into the Private Sector, We Failed”: Why Universities and Companies Need to Rethink the Role of the PhD

 This is part 4 of a 5-part series on university/corporate partnerships in analytics and data science. In addition to this article, Dr. Priestley will also present on this topic at Predictive Analytics World for Business in Las...

Looking At The Numbers in COVID-19

 Like many of you, my focus during this crisis has been less on analytics and more about family, friends, etc. which on a more positive note seems to gain greater emphasis as we reassess our priorities.  But...

Some Thoughts on Analytics in a Post COVID-19 Environment

 In these most difficult times, the use of analytics is certainly not top of mind for most organizations unless it is being used to combat the virus. The challenging scenarios of meeting payroll and having access to...

Re-examining Model Evaluation: The CRISP Approach

 The performance of prediction models can be judged using a variety of methods and metrics. Some years ago, I was challenged to arrive at a set of rules that would provide both the analyst and marketer guidance...

Exploring Gender Imbalance in AI: Numbers, Trends, and Discussions

 Originally pubished in Medium, March 13, 2020 March is Women’s History Month in the US, the UK and Australia, a time to honour women’s sometimes underrated contributions to society. According to the US National Women’s History Museum,...

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