Models Demystified

Michael Clark is a senior machine learning scientist for OneSix, and in prior stints, was a data science consultant at the University of Michigan and Notre Dame. His models have been used in production across a variety of industries, and can be seen in dozens of publications across several academic disciplines. He has a passion for helping people of all skill levels learn difficult stuff.Seth Berry is the Academic Co-Director of the Master of Science in Business Analytics (MSBA) Residential Program, and Associate Teaching Professor at the University of Notre Dame for the IT, Analytics, and Operations Department. He has a PhD in Applied Experimental Psychology, and has been teaching and consulting in data science for over a decade.

• 1.Introduction2.Thinking About Models3.The Foundation4.Understanding the Model5.Understanding the Features6.Model Estimation and Optimization7.Estimating Uncertainty8.Generalized Linear Models9.Extending the Linear Model10.Core Concepts in Machine Learning11.Comon Models in Machine Learning12.Extending Machine Learning13.Causal Modeling14.Dealing with Data15.Danger Zone16.Parting Thoughts