• Advanced Machine Learning taught by Ross Jacobucci on May 5-7. This seminar builds off of our introductory Machine Learning course (see below), covering advanced topics for researchers already familiar with topics like regularization in regression, cross-validation, and decision trees. You'll learn state-of-the-art algorithms for prediction problems with a single outcome, including how to run them and interpret the results, as well as a host of algorithms developed for different types of unsupervised learning tasks.
• Machine Learning taught by Kevin Grimm on May 10-13. This seminar is an excellent introduction to machine learning basics. If you would like to effectively explore your data through machine learning methods, this seminar is for you. 

Both livestream seminars will be held via Zoom, but you can also join asynchronously by viewing the recorded videos of each session. Recordings are accessible for four weeks after the course.

Please share this information with any colleagues, grad students, or others who may be interested. Email ashley@statisticalhorizons.com with any questions.

Thanks,
Ashley