Machine Learning Times
Machine Learning Times
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Visualizing Decision Trees with Pybaobabdt
 Originally published in Towards Data Science, Dec 14, 2021....
Correspondence Analysis: From Raw Data to Visualizing Relationships
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Podcast: Four Things the Machine Learning Industry Must Learn from Self-Driving Cars
    Welcome to the next episode of The Machine...
A Refresher on Continuous Versus Discrete Input Variables
 How many times have I heard that the most...
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1 year ago
“Doing AI” Is a Mistake that Detracts from Real Problem-Solving

  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 with the ultimate business-savvy antidote: how to effectively identify and solve real-world problems. His book will repeatedly make you go “hmm!” as it overhauls your thinking about AI, machine learning, and problem-solving in general. And by the way, if you’d like to hear

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