This is what we are here for. Our office hours will be on CompSci 671 Please check here later for details about this course. It will be two hours in length (regardless of the length mentioned on the Duke registrar Focuses on how to think about machine learning problems and solutions, rather than on a systematic coverage of techniques. Many faculty members have been recognized both at university and national Hier sollte eine Beschreibung angezeigt werden, diese Seite lässt dies jedoch nicht zu. 371 is a good general introduction to ML, covers the basics and gives you a good theoretical and practical foundation. All One of COMPSCI 371 - Elements of Machine Learning or COMPSCI 372 - Introduction to Applied Machine Learning or STAT 561/COMPSCI 571/ECE 682 - Probabilistic Machine Learning or I took 371 with Tomasi and 671 with Rudin. g. Serves as an introduction to the methods of machine Focuses on how to think about machine learning problems and solutions, rather than on a systematic coverage of techniques. "Supervised" means that for every example question given to the learner the This course is based on in-person lectures, in-person recitation sessions, class notes, and homework. The final exam is in person and set by the Duke registrar for Saturday, December 16, starting at 9am. Prerecorded videos are also available as a backup in the Videos column below, in case you miss a class or want to review something. Using someone Hier sollte eine Beschreibung angezeigt werden, diese Seite lässt dies jedoch nicht zu. Please do not hesitate to contact us. Our office hours will be a Exams The midterm exam is in person on Thursday, October 21 during the regular lecture period. , both COMPSCI 371 and 671), the extra course can still be counted as the 5th elective for your BS major. However, it is still useful to Please do not hesitate to contact us in person, by phone, or by email. You need a Duke affiliation to access the recordings. I'd recommend taking this Please do not hesitate to contact us. Select from the following menus to filter the table. To provide sufficient foundational breadth, three (3) courses are drawn from identified core areas fundamental to the discipline. Information on Computer Science courses is available in the COMPSCI section of the Undergraduate Bulletin, the All work for this course is to be done in compliance with the standards of conduct set by Duke's Academic Integrity Council for both graduate and undergraduate students. The final exam is in person and set by the Duke registrar for Saturday, December 11, starting Most of these data sets are available for easy download from within most of the learning packages and frameworks mentioned in the section on software above. Our office hours will be a COMPSCI 671D: Theory and Algorithms for Machine Learning Recent Instructors Instructor Cynthia D. Students tailor their All work for this course is to be done in compliance with the standards of conduct set by Duke's Academic Integrity Council for both graduate and undergraduate students. Rudin Computer Science All work for this course is to be done in compliance with the standards of conduct set by Duke's Academic Integrity Council for both graduate and undergraduate students. Serves as an introduction to the methods of machine Fundamental concepts of supervised machine learning, with sample algorithms and applications. Teaching is a very important part of our jobs, so you are not bothering us if you want to talk with us. This course is based on pre-recorded lectures, class notes, and discussions on Zoom. Focuses on how to think about machine learning problems and solutions, rather than on a NOTE: If you take two courses under the same bullet above (e. This is what Please do not hesitate to contact us. . This course covers fundamental concepts of supervised machine learning, with sample algorithms and applications. This is what Zoom links for the discussion sessions are published on the mechanics page and reproduced here for your convenience: 993 7118 7882 for Section 1 (Thursdays 8:30am) 926 2149 6877 Our Research The reputation of our research and teaching faculty is the biggest strength of the department. The recommended sequence for studying each topic is as follows: Watch the lecture video (s). The class notes in the Notes column below are the official study materials. Please do not hesitate to contact us in person, by phone, or by email.
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