Critics describe machine learning as a “black box”, where data goes in and a prediction comes out, without visibility into how the prediction was derived. This lack of transparency makes it difficult to evaluate and update predictive models as conditions change or new sources of data become available. But today’s machine learning systems are not black boxes, allowing data scientists and business professionals alike to understand how a model makes its predictions.
In this 60-minute webinar, we'll show you:
- Why machine learning is replacing generalized linear models and statistical modeling in many data science efforts
- How today's automated machine learning systems provide the information and visualizations that deliver deep insights that break out of the black box
- The elements of machine learning transparency and a demonstration of DataRobot's visualizations and tools for insights