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Livestream Seminar

Machine Learning

A 4-Day Livestream Seminar Taught by

Kevin Grimm
Course Dates: Ask about upcoming dates
Schedule: All sessions are held live via Zoom.
10:30am-12:30pm ET (New York time): Live session via Zoom
1:30pm-3:00pm ET: Live session via Zoom

This seminar is currently sold out. It will be taught by Seth Flaxman on August 2-5; click here to register. Or email info@statisticalhorizons.com to be added to the waitlist for the May course.

Machine learning has emerged as a major field of statistics and data analysis where the goal is to create reliable and flexible predictive models. This seminar offers a thorough introduction to machine learning methods. Topics covered include: cross-validation; multiple regression; basic variable selection methods; an overview of the R statistical framework; and advanced variable selection methods for regression analysis.

Starting May 10, we are offering this seminar as a 4-day synchronous*, livestream workshop held via the free video-conferencing software Zoom. Each day will consist of two lecture sessions which include hands-on exercises, separated by a 1-hour break. Participants are encouraged to join the lecture live, but will have the opportunity to view the recorded session later in the day if they are unable to attend at the scheduled time.

*We understand that scheduling is difficult during this unpredictable time. If you prefer, you may take all or part of the course asynchronously. The video recordings will be made available within 24 hours of each session and will be accessible for four weeks after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously.

Closed captioning is available for all live and recorded sessions.

More details about the course content

Computing

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Seminar outline

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"Very attentive to our needs and difficulties..."

“Kevin was an excellent tutor! Very attentive to our needs and difficulties, very patient and always helpful. Topics were all very interesting. Examples were worked through in detail. Recommended for both beginners and advanced learners!”

Panagiotis Ferentinos

National and Kapodistrian University of Athens

“I can’t tell you how much I enjoyed the course!"

“I can’t tell you how much I enjoyed the course! Dr. Grimm did a great job. He is superb! He covered the machine learning algorithms and approaches thoroughly, and taught in such a way that it was easy to understand. Another amazing fact is that he not only provided the detailed R code and but also went through the code during the lectures and labs. The lectures were very engaging. I attended this workshop for my own interest and for my research program. I thoroughly enjoyed!”

Saumen Mandal

University of Manitoba

"Covers a lot of different examples and methods."

“I really enjoyed the course. Great teacher. Covers a lot of different examples and methods. Can be used and adapted to my own work very quickly. 5 star recommendation.”

Stefan Gross

University Medicine Greifswald

"His expertise in latent variable modeling also allows for fruitful cross-disciplinary exchanges."

“The course addresses the most important supervised machine learning algorithms and approaches in a clear and comprehensive way. Professor Kevin Grimm provides excellent and clear explanations, as well as a plethora of useful material. His expertise in latent variable modeling also allows for fruitful cross-disciplinary exchanges. I highly recommend this course to anyone interested in deepening his/her expertise in this area.”

Enrico Perinelli

University of Trento