Machine Learning Interpretability with Driverless AI – insideBIGDATA

Machine Learning Interpretability with Driverless AI – insideBIGDATA

Machine Learning Interpretability with Driverless AI – insideBIGDATA
In this presentation, our friends Andy Steinbach, Head of AI in Financial Services at NVIDIA, and Patrick Hall, Senior Director of Product at H2O.ai discuss Machine Learning Interpretability with Driverless AI. Interpretability is a hugely popular topic in machine learning. Wherever possible, interpretability approaches are deconstructed into more basic components suitable for human storytelling: complexity, scope, understanding, and trust.

Source:: https://plus.google.com/+ChristianContardi/posts/ZoX5RbTaFoH

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