Deep Learning 2024#

Literature#

  1. Probabilistic Machine Learning: An introduction. [Murphy, 2022]

  2. Deep Learning [Goodfellow, Bengio, and Courville, 2016]

  3. Understanding Deep Learning [Prince, 2023]

  4. Dive into Deep Learning [Zhang, Lipton, Li, and Smola, 2023]

  5. ML Handbook

Course assessment#

Activity

Final scores

Attendance

\(10\%\)

Practice (labs)

\(30\%\)

Midterm

\(10\%\)

Endterm

\(10\%\)

Final exam (project)

\(40\%\)

Invite to MS Teams: rvnmeqz

Project#

Create a group project that solves a real-world problem based on deep learning algorithms. Recommended team size is 2-3 students.

Final project proposal (deadline 8th week):#

  • Title: the problem which is going to be solved

  • Settling team members roles (data preparation, coding, team leading, etc)

  • Link to the dataset (open source is better)

  • Architecture or algorithms that you are going to use

  • Evaluation methods

  • Reference

Report#

  • Motivation and Objective (Problem, Challenge)

  • Related Work and Originality

  • Design Architecture

  • Detailed Algorithm or Functions

  • Coding

  • Results and Performance Evaluation

  • Conclusion

  • Reference

  • Roles of Members

  • Bonus: make your work visible (GitHub, YouTube, etc)

Final project presentation (examination week)#

  • 15 min for presentation + 5 min QA

  • Demo in Jupyter Notebook

  • All group members should participate during the presentation

The topic can be changed not later than 12th week with providing a new proposal.