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), […]
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 […]
About the course Scaling applications to multiple GPUs across multiple nodes requires one to be adept at programming models and optimization techniques, and proficient at performing root-cause analysis using in-depth profiling to identify and minimize bottlenecks. The Multi-GPU Programming Bootcamp covers step-by-step ways to improve application performance using cues from profilers and provides an understanding […]
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 .
