Hasso-Plattner-Institut
Prof. Dr. Tobias Friedrich
 

Competitive Programming with Deep Learning 2

MSc Project Seminar - Winter 2022/23

Overview

In this course we will participate in AI (online) competitions using, for example, the Kaggle platform. Please note that this course will be held fully online. Please keep in mind that there is a participants limitation for this course.

Description

In this course, participants (in teams) enter various AI competitions. Thereby, we offer two variations of competitions for the students to participate in: Kaggle competitions or research-oriented competitions. In the former, you participate in a few Kaggle online competitions together with thousands of AI programmers world-wide. The Kaggle competitions will be a good chance for you to practice known deep learning algorithms (as well as other ML techniques) and learn new ones. For the research-oriented competitions, you will elaborate possible (novel) solutions to existing problems, battling with existing state-of-the-art papers.

In both settings, you are free to use any programming language, any libraries, any framework (Pytorch, Keras, Tensorflow, fast.ai, whatever you prefer) and any algorithms (ML or deep learning or even heuristics) as you like. The goal in these competitions will be to maximize your points in the competition.

During the competition, we will assist and guide you (and your team) with weekly meetings, were we discuss possible approaches and the best course of action. There will also be a written part (a short scientific report) where you and your team write about your findings for a selected competition.

Requirements

There are no formal requirements, however, participants are expected to know the basics of deep learning as there will be no teaching part.

Please be aware that this course is taught in English.

Grading

The evaluation of the course is based on the performance on the competition and research-oriented part (split 50/50). Note that both parts include a short report as well.

Dates

We meet online weekly on Tuesday, at 13:30 - 15:00. The technical details for these meetings will be shared via moodle.

Lecture Team

The following persons are involved in this lecture:

Dr. Sarel Cohen

Lecturer

Office: K-2.18
E-Mail: Sarel.Cohen(at)hpi.de

Dr. Davis Issac

Lecturer

Office: K-2.07
E-Mail: Davis.Issac(at)hpi.de

Teaching Assistant

Office: K-2.09/10

E-Mail: Vanja.Doskoc(at)hpi.de

Teaching Assistant

Office: K.2-19/20
E-Mail: Aishwarya.Radhakrishnan(at)hpi.de