Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
The Great AI Myth: These 3 Misconceptions Fuel It
 Originally published in Forbes, July 29, 2024. The hottest thing...
How to Sell a Machine Learning Project
 Originally published in Built In, February 6, 2024. Never...
The 3 Things You Need To Know About Predictive AI
 Originally published in Forbes, June 29, 2024. Some problems are...
Alphabet Uses AI To Rush First Responders To Disasters—Takeaways For Businesses
 Originally published in Forbes, July 7, 2024. The National Guard...

Eric Siegel

Wise Practitioner – Predictive Analytics Interview Series: Nishant Sharma at Charter Communications

 In anticipation of his upcoming conference presentation, Model Based Fiber Network Expansion at Predictive Analytics World for Business Las Vegas, June 3-7, 2018, we asked Nishant Sharma, Director, Predictive Analytics at Charter Communications, a few questions about his work in predictive analytics. Q: In your work with predictive analytics, what behavior or outcome do your models

Wise Practitioner – Predictive Analytics Interview Series: Theresa Kushner at Dell EMC

 In anticipation of her upcoming conference presentation, Using Machine Learning to Move the Enterprise, at Predictive Analytics World for Business Las Vegas, June 3-7, 2018, we asked Theresa Kushner, SVP, Business Intelligence at Dell EMC, a few...

Wise Practitioner – Predictive Analytics Interview Series: Ron Cowan at Snowforce Data

 In anticipation of his upcoming conference presentation, Using Mileage Logs to Predict Successful Sales Behavior at Predictive Analytics World for Business New York, Oct 29-Nov 2, 2017, we asked Ron Cowan, Founder at Snowforce Data, a few...

The Harvard Business Review Video Interview: Eric Siegel on Predictive Analytics

 Originally published by Harvard Business Review If the video is not showing, click here to view linked to:  https://hbr.org/webinar/2017/09/putting-predictive-analytics-to-work Prediction is reinventing industries and changing our worlds. Companies, governments, law enforcement agencies, hospitals, and universities are using the...

Wise Practitioner – Predictive Analytics Interview Series: Anasse Bari, New York University

  Wall Street and the New Data Paradigm In anticipation of his upcoming conference presentation, Wall Street and the New Data Paradigm at Predictive Analytics World for Financial in New York, Oct 29-Nov 2, 2017, we asked...

Data Science: Screening by Religion a Blunt Instrument for Security

 This commentary first appeared in the San Francisco Chronicle. Originally published as the cover piece for the Insight commentary section in the Sunday San Francisco Chronicle, this op-ed by Eric Siegel points out that, although many believe...

Wise Practitioner – Predictive Analytics Interview Series: Steve Weiss, at LinkedIn

In anticipation of his upcoming conference presentation, The Sprint for Teaching Data Science: LinkedIn Learning, Analytics and the New Era of Just-In-Time Skills Training at Predictive Analytics World for Business New York, Oct 29-Nov 2, 2017, we...

Wise Practitioner – Predictive Analytics Interview Series: Emilie Lavoie-Charland at The Co-operators

 In anticipation of her upcoming conference presentation, Which Predictive Model Will Best Help Increase Retention? at Predictive Analytics World for Business New York, Oct 29-Nov 2, 2017, we asked Emilie Lavoie-Charland, Research & Innovation Analyst at The...

Wise Practitioner – Predictive Analytics Interview Series: Leslie Barrett at Bloomberg L.P.

 In anticipation of her upcoming conference presentation, Crowd-Sourcing and Quality: How To Get The Best Out of Hand-Tagged Training Data for Machine Learning Models at Predictive Analytics World for Business New York, Oct 29-Nov 2, 2017, we...

Why Data Science Argues against a Muslim Ban

 From the perspective of data science, a Muslim ban would weaken security, not strengthen it (click for additional articles by Eric Siegel on analytics and social justice). Originally published by Scientific American June 14, 2017 Let’s not...

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