Глубинное обучение (курс лекций)/2019
Материал из MachineLearning.
This is an introductory course on deep learning models and their application for solving different problems of image and text analysis.
Instructors: Dmitry Kropotov, Victor Kitov, Nadezhda Chirkova, Oleg Ivanov and Evgeny Nizhibitsky.
The timetable in Autumn 2019: Mondays, lectures begin at 10-30, seminars begin at 12-15, room 526b.
News
06 Sep: First theoretical assignment is uploaded to anytask. Deadline: 15 Sep. Please note: this is a strict deadline, no delay is possible.
Rules and grades
We have several practical assignments during the course. For each assignment, a student may get up to 10 points + possibly bonus points. A student is allowed to upload his fulfilled assignment during one week after deadline with grade reduction of 0.2 points per day. All assignments are prepared in English.
Also each student may give a small 10-minutes talk in English on some recent DL paper. For this talk a student may get up to 5 points.
The total grade for the course is calculated as follows: Round-up (0.3*<Exam_grade> + 0.7*<Semester_grade>).
Practical assignments
Practical assignments are provided on course page in anytask.org. Invite code: IXLOwZU
Lectures
| Date | No. | Topic | Materials |
|---|---|---|---|
| 02 Sep. 2019 | 1 | Introduction. Fully-connected networks. | |
| 09 Sep. 2019 | 2 | Optimization and regularization in deep learning |
Seminars
| Date | No. | Topic | Need laptops | Materials |
|---|---|---|---|---|
| 2 Sep. 2019 | 1 | Matrix calculus, automatic differentiation. | No | |
| 9 Sep. 2019 | 2 | Introduction to Pytorch | Yes |
