It can be difficult to understand how predictive models operate and how they make decisions. Moreover, hidden inside them may be biases that both skew your conclusions and result in uneven or unfair treatment for some people.
What does it mean to look inside your models, and what are some tools you can use to understand how they work? And, most importantly — why should you care? Join us to discuss key issues of interpretability, bias and impact in predictive analytics.