Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Three Best Practices for Unilever’s Global Analytics Initiatives
    This article from Morgan Vawter, Global Vice...
Getting Machine Learning Projects from Idea to Execution
 Originally published in Harvard Business Review Machine learning might...
Eric Siegel on Bloomberg Businessweek
  Listen to Eric Siegel, former Columbia University Professor,...
Effective Machine Learning Needs Leadership — Not AI Hype
 Originally published in BigThink, Feb 12, 2024.  Excerpted from The...

data analytics

Why Machine Learning is Central to Reverse Supply Chain 2.0

  E-commerce growth and a worldwide pandemic have brought to light the inefficiencies in the modern supply chain, especially the return process. The current return process is costly, inefficient, and wasteful. The following article explores how enabling efficient returns through reverse supply chain development can bring savings and operational improvements. Most companies are failing to

97 Things About Ethics Everyone In Data Science Should Know

 Every now and then an opportunity comes along that you just can’t pass up. One such opportunity that fell into my lap was when O’Reilly media reached out to me to see if I was interested in...

Research Summary: Health Care, Capabilities, and AI Assistive Technologies

 Originally published in MAIEI, May 3, 2020. The adoption of AI-enabled solutions in the healthcare industry has accelerated with the ongoing pandemic and while there are a lot of concerns raised, most quite aptly, there is a...

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...

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