6 ways to make machine learning fail

What a successful AI team really looks like Email not displaying correctly? View it in your browser.

IDG AI/Machine Learning Report Our top picks from IDG's editors Oct 11, 2018 6 ways to make machine learning fail When learning, machine learning will make mistakes. Adopters need to anticipate that—and be careful not to make matters worse through human mistakes by IT and business Read More ▶ Your Must-Read Stories • What a successful AI team really looks like • Machine learning: How to go from theory to reality • PyTorch 1.0 accelerates Python machine learning with native code • Overcoming the hype around predictive analytics for better business outcomes • Microsoft smartens up the ML.Net machine learning API What a successful AI team really looks like Forget the tech giants' rosters of data science PhDs. As AI moves into the enterprise, blended teams with business skills become more important for driving business value. Read More ▶ Machine learning: How to go from theory to reality A lack of skilled people continues to stymie the AI revolution. That's why smart companies invest as much in cultural change as technology adoption—and Google shows how Read More ▶ PyTorch 1.0 accelerates Python machine learning with native code The PyTorch 1.0 release candidate introduces Torch Script, a Python subset that can be JIT-compiled into C++ or other high-speed code Read More ▶ Overcoming the hype around predictive analytics for better business outcomes As data-driven solutions become the norm, enterprises need to know exactly what's going on behind all those buzzwords. Read More ▶ Microsoft smartens up the ML.Net machine learning API Microsoft's TensorFlow-compatible machine learning framework debuts a reworked API for more flexible pipelines and improved prediction performance Read More ▶

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