Summary: If you’re planning your AI/ML business strategy watch out for the confusion in categories and overly risky ratings given by some research and review sources. Read the research, then consult with your own data scientists for a better evaluation of risk. It’s likely not as bad as you think.
ContinueAdded by William Vorhies on March 2, 2020 at 12:42pm — No Comments
Summary: Not enough labeled training data is a huge barrier to getting at the equally large benefits that could be had from deep learning applications. Here are five strategies for getting around the data problem including the latest in One Shot Learning.
For at least the last two years we’ve been in an…
Added by William Vorhies on January 28, 2019 at 9:56am — 1 Comment
Summary: We are entering a new phase in the practice of data science, the ‘Code-Free’ era. Like all major changes this one has not sprung fully grown but the movement is now large enough that its momentum is clear. Here’s what you need to know.
We are entering a new phase in the practice of data science, the ‘Code-Free’…
Added by William Vorhies on October 9, 2018 at 9:54am — 3 Comments
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Posted 12 April 2021
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