April 14th, 2021 – Due to popular demand and to strengthen inclusion, we have extended the deadline for registration until April 21st.
March 15th, 2021 – Registration has been opened. Please use the form available in the registration tab to start the process!
International Summer School on Deep Learning 2021
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.
Day 1 – If you have some background in programming but you have no experience in neural networks join us for the FIRST DAY WORKSHOP on fundamentals of DEEP LEARNING. The Workshop will introduce you to the basics of neural networks as a practical method of machine learning, focusing further on convolutional neural networks and best practices.
Days 2-4 – During the remaining three 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.
Day 5 – Conference on AI inference in practice (no additional fee for attendees of the School): Are you familiar with basic aspects of Deep Learning? Great! You will have the opportunity to join us during the 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 4-6 – IEEE Human System Interaction (HSI) conference (July 8-10) – The conference will cover the theory, design and application of human‐system interactions in the areas of science, education, business, industry, services, humanity, environment, health, and government. Aside from the regular presentations, the conference will include keynote addresses from speakers who work both in industry and academia, and expects to attract more than 120 participants.
More details on how to participate in the HSI conference will be provided soon.
More information: 14th International Conference on Human System Interaction (welcometohsi.org)
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.
Jacek Ruminski, prof. GUT
Training Program Chair
Alicja Kwasniewska, SiMa.ai
Maciej Szankin, Intel