Welcome

We are pleased to invite you to the third edition of the International Summer School on Deep Learning!

Latest news

[10/02/2020] Registration is now open!
After submitting the registration form you should expect confirmation e-email. If you don’t see the message please check in the spam folder (look for message with subject ” ISSonDL 2020 Registration confirmation” or ” ISSonDL 2020 Conference Registration confirmation”).
Decision about acceptance should be send no later than 18.03.2020.

[07/02/2020] Grants (only for PhD students – applications until 3rd March 2020)
There is an opportunity to apply for a small grant to cover some travel/stay costs. Please find more information at: https://pg.edu.pl/prom/main-page. Please contact only with the contact people listed at this website.


International Summer School on Deep Learning will introduce participants with fundamentals of deep learning methods. Outside of the base camp, special sessions and keynotes are planned to keep the audience up to date with the latest advances in this fascinating research area. Outstanding speakers and experienced instructors from all over the world will present scientific background, practical issues and perspectives for the future of deep learning methods. The keynote lectures and mini courses will cover topics ranging from fundamentals of neural networks to practical implementations and applications of deep learning. We invite students, researchers and professionals to participate in this unique event that will keep you on track, help unleashing new ideas and give you a chance to be a part of mind-blowing conversations.

School Highlights

First day – On the first day of the School we will have two parallel tracks to choose from depending on your experience and interests:

  1. Introduction to Deep Learning: If you have some background in programming but you have no experience in neural networks join us during the FIRST DAY WORKSHOP on fundamentals of DEEP LEARNING. The Workshop will introduce you with the basics of neural networks as a practical method of machine learning, focusing further on convolutional neural networks and recurrent neural networks.
  2. Conference on AI inference in practice: Are you familiar with basic aspects of Deep Learning? Great! You will have the opportunity to join us during one-day conference focused on Deep Learning models in action. In this track you will learn how to use models in real life scenarios, what edge platforms are available on the market for AI inference and how to implement a model in a mobile application (e.g. in Android).

Days 2-5 – During the remaining four days of the School you will have a chance to dive deep into Deep Learning trends and applications by taking part in hands-on workshops and keynotes. Sessions will cover algorithms used for data processing in vision, text, audio and other domains.

Why to attend

  • Hands-on: One of the main goals of this event is gaining practical experience to put deep learning theory into practice and make it more relevant for all attendees. Running your own experiments will be possible with interactive course resources available online, so do not forget to take your mobile computer with you!
  • Cutting edge platforms: Recent hardware solutions, including NVIDIA DGX Station and Intel-based platforms, will be presented and used to run experiments during live sessions.
  • Interactive: During the event, participants will have a chance to be involved in the conversations and exchange ideas not only during scientific meetings but also during get together parties.
  • Challenges: During the event you will have a chance to participate in exciting challenges. Winners will be awarded with certificates and valuable prizes.
  • Certificates: All participants actively taking part in the training will receive a certificate with detailed information about learnt topics and attended training hours.
  • Cost-effective: About 40 university hours of trainings will be provided for an affordable price.

Organizers

General Chair
Jacek Ruminski, prof. GUT
jacek.ruminski@pg.edu.pl

Training Program Chair
Alicja Kwasniewska, Intel and GUT
alicja.kwasniewska@intel.com

Publicity Chair
Maciej Szankin, Intel
maciej.szankin@intel.com

Organizing Committee