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Machine Learning - Online Course

A 4-Day Livestream Seminar Taught by

Seth Flaxman
Course Dates: Ask about upcoming dates
Schedule: All sessions are held live via Zoom. All times are ET (New York time).
10:30am-12:30pm ET (convert to your local time)
1:30pm-3:00pm ET
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Machine learning has emerged as a major field at the intersection of statistics and computer science where the goal is to create reliable and flexible predictive models. This seminar offers a thorough introduction to supervised machine learning methods. Topics covered include: supervised learning; loss functions and optimization; cross-validation; the bias/variance tradeoff; high-dimensional variable selection and regularization methods; non-linear methods such as random forests and support vector machines; an introduction to deep learning; and an overview of the R programming language.

Starting August 2, 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. You are encouraged to join the lecture live, but will have the opportunity to view the recorded session later in the day if you are unable to attend at the scheduled time.

*We understand that finding time to participate in livestream courses can be difficult. 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.

This course is designed for those who have no previous experience with machine learning. If you are looking to learn more advanced methods, check out Advanced Machine Learning.

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