Originally published in KDnuggets. The latest KDnuggets poll reconfirms today’s dire industry buzz: Very few machine learning models actually get deployed. In this article, I’ll summarize the poll results and argue that this pervasive failure of ML projects comes from a lack of prudent leadership. I’ll also argue that MLops is not the fundamental
A note from Executive Editor Eric Siegel: In this book review, Rich Heimann concludes that the concept of “AI First” only perpetuates the fallacy of AI as a single solution, not to mention continuing the hype...
Event: Machine Learning Week 2021 Keynote: Career Paths in Analytics and Data Science and Analytics Team Building Speaker: Meghan Anzelc, Head of Data & Analytics, Spencer Stuart Bio: Meghan Anzelc Head of Data & Analytics Meghan joined Spencer Stuart in...
Do your models usually get deployed? Or are many of even your best models never actually launched into production? We want to know: What Percentage of Your Machine Learning Models Have Been Deployed? Industry buzz indicates...
Event: Machine Learning Week 2021 Keynote: Credit Models, Microfinance, and Improving the Lives of Families in the Developing World Speaker: Aric LaBarr, Associate Professor of Analytics, Institute for Advanced Analytics at NC State University Bio: A Teaching Associate Professor in the Institute...
Event: Machine Learning Week 2021 Keynote: Identifying Program Effectiveness for Survivors of Human Trafficking and Slavery Speaker: Muneeb Alam, Specialist, Data Science, QuantumBlack, a McKinsey company Bio: Muneeb Alam is a data science specialist at QuantumBlack, a McKinsey Company. He...
Event: Machine Learning Week 2021 Keynote: How to Use AI Ethically Speaker: Natalia Modjeska, Research Director at Omdia (part of Informa Tech) Bio: Natalia Modjeska is a Research Director at Omdia (part of Informa Tech) where she leads the team...
Event: Machine Learning Week 2021 Keynote: Alexa On The Edge – A Case Study in Customer-Obsessed Research Speaker: Nathan Susanj, Applied Science Manager at Amazon Bio: Previously Nathan was a data scientist on the Wells Fargo Enterprise Analytics and...
Should data scientists consider AI a threat to their short- or even long-term job security? In this article, I present a philosophical argument that adamantly argues, “No.” For the work of data scientists, and human endeavors in...
A note from Executive Editor Eric Siegel: Richard Heimann’s forthcoming book, Doing AI, takes on the problems with “AI” as a brand with a style so crisp, clear, and unique, it just pops off the page....
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