Learning from Data (Fall 2020)Welcome to the class website of Learning from Data! Announcement
2020-12-3: The guest lecture, given by Pedro Baiz, will be given from 10:00am - 11:00 am at Info Building rom 510. 2020-10-29: The midterm exam will be held in class on Friday, November 6th. For anyone who can not attend the in-class exam, please contact a TA to fill out the online exam application before Nov 3rd. 2020-09-28: The make-up lecture for the National holiday will be held on Sunday, Sept 28th at 9:20am 2020-09-09: Since the first scheduled class conflicts with the Graduate School Admission Interview, the first class is switched to Sunday morning. Class info
For more information about grading, homework and exam policies, see the class syllabus. DescriptionThis introductory course gives an overview of many concepts, techniques, and algorithms in machine learning, beginning with topics such as logistic regression and SVM and ending up with more recent topics such as deep neural networks and reinforcement learning. The course will give the student the basic ideas and intuition behind modern machine learning methods as well as a bit more formal understanding of how, why, and when they work. The underlying theme in the course is statistical inference as it provides the foundation for most of the methods covered. PrerequisitesBasic concepts in calculus, probability theory, and linear algebra. TeamInstructor:
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