Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Survey: Machine Learning Projects Still Routinely Fail to Deploy
 Originally published in KDnuggets. Eric Siegel highlights the chronic...
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,...

Machine Learning

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 the bombardment of news regarding this crisis certainly focuses on numbers in terms of providing a perspective of

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,...

The 5 Classification Evaluation Metrics Every Data Scientist Must Know. And when Exactly to Use Them?

 Originally pubished in Medium, Sept 17, 2019. What do we want to optimize for? Most of the businesses fail to answer this simple question. Every business problem is a little different, and it should be optimized differently....

Is What You Did Ethical? Helping Students in Computational Disciplines to Think About Ethics

 In addition to this article, Dr. Priestley will also present on this topic at Predictive Analytics World for Business in Las Vegas, May 31-June 4, 2020. For details about her session, “How Leading Enterprises Leverage Universities to...

The New Business of AI (and How It’s Different From Traditional Software)

 Originally published in a16z.com February 16, 2020 At a technical level, artificial intelligence seems to be the future of software. AI is showing remarkable progress on a range of difficult computer science problems, and the job of...

Predicting the President: Two Ways Election Forecasts Are Misunderstood

  Originally published by Big Think When it’s a presidential election year, speculation is in the cards. It’s the national pastime. Everyone wants to predict who’ll win. But, man, did people mismanage their own expectations leading up...

Is Machine Learning Always The Right Choice?

 Since this article will probably come out during Income tax season, let me start with the following example: Suppose we would like to build a program that calculates income tax for people. According to US federal income...

Remember FindFace? The Russian Facial Recognition Company Just Turned On A Massive, Multimillion-Dollar Moscow Surveillance System

  Originally published in Forbes.com, January 29, 2020 Built on several tens of thousands of cameras and what’s claimed to be one of the most advanced facial recognition systems on the planet, Moscow has been quietly switching...