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

Building a Diverse Workforce for Next-Generation Analytics and AI

 Originally published in HPCWire, October 15, 2018 High-performance computing (HPC) has a well-known diversity problem, and groups such as Women in HPC are working to address it. But while the diversity challenge crosses the science and technology spectrum, it is especially acute in areas of HPC where breakthroughs are driven by extracting insights from data.

Dr. Data Show Video: How Can You Trust AI?

 Watch the second episode of The Dr. Data Show, which answers the question, “How can you trust artificial intelligence?” About the Dr. Data Show. This new web series breaks the mold for data science infotainment, captivating the...

Three Common Mistakes That Can Derail Your Team’s Predictive Analytics Efforts

  Originally published by Harvard Business Review With today’s high demand for data scientists and the high salaries that they command, it’s often not practical for companies to keep them on staff.  Instead, many organizations work to...

Artificial Intelligence: Are We Effectively Assessing Its Business Value?

 As most data science practitioners know, artificial intelligence (AI) is not new and has been explored by academia back as far back as the fifties. The real core of AI is the branch of mathematics related to...

The Growing Participation of Women in the Data Science Community

 Originally published in KDNuggets, September 2018 Research indicates data science is a promising career path, and it’s a field likely to offer job security and growth for the foreseeable future. Women are still significantly underrepresented, though. Statistics...

Deep Learning Framework Power Scores 2018—Who’s On Top in Usage, Interest, and Popularity?

 Originally published in Towards Data Science  September 19, 2018 For today’s leading deep learning methods and technology, attend the conference and training workshops at Deep Learning World, June 16-19, 2019 in Las Vegas.  Deep learning continues to...

Dr. Data Show Video: Why Machine Learning Is the Coolest Science

 Watch the premiere episode of The Dr. Data Show, which answers the question, “What makes machine learning the coolest science?” About the Dr. Data Show. This new web series breaks the mold for data science infotainment, captivating...

Blatantly Discriminatory Machines: When Algorithms Explicitly Penalize

 Originally published in The San Francisco Chronicle (the cover article of Sunday’s “Insight” section) What if the data tells you to be racist? Without the right precautions, machine learning — the technology that drives risk-assessment in law...

How Netflix Uses Big Data to Drive Success

 Originally published in insideBIGDATA  January 20, 2018. Netflix has over 100 million subscribers and with that comes a wealth of data they can analyze to improve the user experience. Big data has helped Netflix massively in their...

Data Reliability and Validity, Redux: Do Your CIO and Data Curators Really Understand the Concepts?

 Here are two recent entries on the big but neglected issue of data reliability and analytic validity (DR&AV), from the vast commentariat that is LinkedIn: One of my complaints with hashtag#bigdata, is there isn’t enough focus on...

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