Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Video – How to Use AI Ethically from Natalia Modjeska of Omdia
 Event: Machine Learning Week 2021 Keynote: How to Use AI...
Video – Alexa On The Edge – A Case Study in Customer-Obsessed Research from Susanj of Amazon
 Event: Machine Learning Week 2021 Keynote: Alexa On The Edge...
Why AI Isn’t Going to Replace Data Scientists Any Time Soon
 Should data scientists consider AI a threat to their...
“Doing AI” Is a Mistake that Detracts from Real Problem-Solving
  A note from Executive Editor Eric Siegel: Richard...

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 Originally published in Eugeneyan. Applying machine learning effectively is tricky. You need data. You...

 Originally published in United AI, Sept 24, 2021. According to new research, one of...

 Originally published in IEEE Spectrum, Oct 4, 2021. Imagine you’re a farmer in the...

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     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 of analysts covering Artificial Intelligence and Intelligent Automation from processors and software to enterprise deployments. Natalia’s journey into […]

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     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 Data Science team where he led a small team as head of Natural Language Processing (NLP) and Speech […]

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     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 general, machines are nowhere near human intellectual capabilities. There has been much discussion, almost euphoric in some instances, […]

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      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. He surveys the litany of troublemakers who’ve misguided the world with AI mythology, but then greets this mishap […]

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      This article is based on the transcript of one of 142 videos in Eric Siegel’s online course, Machine Learning Leadership and Practice – End-to-End Mastery. Originally published by SAS Blogs How do you internally sell a machine learning project and get the green light? It’s time to put on your business-professional hat and make […]

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    Organizations often miss the greatest opportunities that machine learning has to offer because tapping them requires real-time predictive scoring.

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      This article is based on the transcript of one of 142 videos in Eric Siegel’s online course, Machine Learning Leadership and Practice – End-to-End Mastery. Developing a good predictive model with machine learning isn’t the end of the story — you also need to use it. Predictions don’t help unless you do something about […]

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