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

The Four Most Common Fallacies About AI

 Originally published in VentureBeat, May 8, 2021. The history of artificial intelligence has been marked by repeated cycles of extreme optimism and promise followed by disillusionment and disappointment. Today’s AI systems can perform complicated tasks in a wide range of areas, such as mathematics, games, and photorealistic image generation. But some of the early goals of AI like housekeeper robots

How Image Search Works at Dropbox

 Originally posted in Dropbox.tech, May 11, 2021 Photos are among the most common types of files in Dropbox, but searching for them by filename is even less productive than it is for text-based files.  When you’re looking...

Inside Netflix’s Quest to End Scrolling – How the Company is Working to Solve One of its Biggest Threats: Decision Fatigue.

 Originally published in Vulture, April 28, 2021.  Ten years ago, Netflix got the idea that its app should work more like regular TV. This was early on in its transition from DVD delivery to streaming on demand,...

Clustergam: Visualisation of Cluster Analysis

 Originally published in MARTIN FLEISCHMANN, April 27, 2021. When we want to do some cluster analysis to identify groups in our data, we often use algorithms like K-Means, which require the specification of a number of clusters....

Aiming for truth, fairness, and equity in your company’s use of AI

 Originally published in FTC, April 19, 2021: Advances in artificial intelligence (AI) technology promise to revolutionize our approach to medicine, finance, business operations, media, and more. But research has highlighted how apparently “neutral” technology can produce troubling...

Moving Beyond “Algorithmic Bias is a Data Problem”

 Originally published in Patterns, April 9, 2021. A surprisingly sticky belief is that a machine learning model merely reflects existing algorithmic bias in the dataset and does not itself contribute to harm. Why, despite clear evidence to the...

Hot Video: More Accuracy Fallacies – Predicting Criminality and Psychosis

 Check out this topical video from Predictive Analytics World founder Eric Siegel: Can AI “tell” if you’re a criminal? Or whether you’ll develop psychosis? These are perfect examples of the accuracy fallacy, which misleads the public into...

The Precondition for Machine Learning Success: Bridge the Quant/Business Culture Gap

  Over the last few years, I poured thousands of working hours and 25 years of consulting and teaching experience into making the online course Machine Learning Leadership and Practice – End-to-End Mastery. Why? I developed this...

Hot Video: The Accuracy Fallacy – Bogus Machine Learning Results

 Check out this topical video from Predictive Analytics World founder Eric Siegel: Can AI “tell” if you’re gay? When machine learning practitioners claim their model achieves “high accuracy,” it’s often bogus. This video reveals the undeniable yet...

Can Artificial Intelligence Combat Wildfires? Sonoma County Tests New Technology

 Originally published in Los Angeles Times, March 19, 2021. Sonoma County is adding artificial intelligence to its wildfire-fighting arsenal. The county has entered into an agreement with the South Korean firm Alchera to outfit its network of...

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