January 2024
Intermediate to advanced
192 pages
2h 27m
English
by Eric Siegel
You might think that news of “major AI breakthroughs” would do nothing but help machine learning’s (ML) adoption. If only. Even before the latest splashes—most notably OpenAI’s ChatGPT and other generative AI tools—the rich narrative about an emerging, all-powerful AI was already a growing problem for applied ML. That’s because for most ML projects, the buzzword AI goes too far. It overly inflates expectations and distracts from the precise way ML will improve business operations.
Most practical use cases of ML—designed to improve the efficiencies of existing business operations—innovate in fairly straightforward ways. Don’t let the glare emanating from this glitzy technology ...
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