171. How to Choose a Model
A short series on the fundamentals of model family selection and model fitting
Choosing the best model to fit your data is an art. In this short course, we step through the mechanics of model evaluation and the subtle trade-offs that different model classes offer.
To see how model selection works in a realistic machine learning problem, check out the Polynomial Regression Course.
I love solving puzzles and building things. Machine learning lets me do both. I got started by studying robotics and human rehabilitation at MIT (MS '99, PhD '02), moved on to machine vision and machine learning at Sandia National Laboratories, then to predictive modeling of agriculture DuPont Pioneer, and cloud data science at Microsoft. At Facebook I worked to get internet and electrical power to those in the world who don't have it, using deep learning and satellite imagery and to do a better job identifying topics reliably in unstructured text. Now at iRobot I work to help robots get better and better at doing their jobs. In my spare time I like to rock climb, write robot learning algorithms, and go on walks with my wife and our dog, Reign of Terror.