Registration Deadline: 24 March 2025 Format: Hybrid (on-site & online) Prerequisites: -Experience in a Linux environment, jupyter notebook, Python, Conda, and BioBB library. -Familiarity with High-Performance Computing (HPC) systems is required for participation in the hands-on sessions. -The training is primarily designed for participants from academia (with at least a graduate degree), industry, or public administration who […]
About this webinar Machine learning is a branch of artificial intelligence that enables computers to learn from data and make predictions or decisions without being explicitly programmed. Multi-label learning is a type of machine learning problem where each data instance can be associated with multiple labels simultaneously. Partial multi-label learning addresses problems where each instance […]
General introduction Deep learning is a subset of machine learning that focuses on training artificial neural networks with multiple layers to recognize patterns and to simulate the complex decision-making power of the human brain. The use of deep learning has seen a significant increase of popularity and applicability over the last decade. While it serves […]
About this webinar Software installation on High-Performance Computing (HPC) systems differs from typical installations on personal computers due to multi-user environments, shared resources, and system-wide configurations.Instead of installing software globally, users often work within shared or isolated environments while leveraging specialized tools for software management.There are multiple methods available to install software on HPC systems […]
About the course The End-to-End AI for Science Bootcamp provides a step-by-step overview of the fundamentals of deep neural networks, walks attendees through the hands-on experience of building and improving deep learning models using a framework that uses the fundamental laws of physics to model the behavior of complex systems (physics-informed neural networks – PINNs), […]
This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 951732. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and its associated countries .
