This lesson gives an introduction to high-performance computing with the Compute Canada network, first providing an overview of use cases for HPC and then a hands-on tutorial. Though some examples might seem specific to the Calcul Québec, all computing clusters in the Compute Canada network share the same software modules and environments.
This talk presents an overview of CBRAIN, a web-based platform that allows neuroscientists to perform computationally intensive data analyses by connecting them to high-performance computing facilities across Canada and around the world.
Introduction of the Foundations of Machine Learning in Python course - Day 01.
High-Performance Computing and Analytics Lab, University of Bonn
Optimization for machine learning - Day 02 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Linear Algebra for Machine Learning - Day 03 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Support Vector Machines - Day 06 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Decision Trees and Random Forests - Day 07 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Clustering and Density Estimation - Day 08 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Dimensionality Reduction - Day 09 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Introduction to Neural Networks - Day 10 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Introduction to Convolutional Neural Networks - Day 11 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Initialization, Optimization, and Regularization - Day 12 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
U-Nets for medical Image-Segmentation - Day 13 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Sequence Processing - Day 15 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
This lecture covers FAIR atlases, including their background and construction, as well as how they can be created in line with the FAIR principles.
This video provides a very quick introduction to some of the neuromorphic sensing devices, and how they offer unique, low-power applications.
In this module you will learn the basics of Brain Computer Interface (BCI). You will read an introduction to the different technologies available, the main components and steps required for BCI, associated safety and ethical issues, as well as an overview about the future of the field.
In this module, users will learn about the different types of neurotechnology and how each of them works. This will be done through the metaphor of going to a symphony... in your brain. Like a symphony, brain processes emerge from collections of neural activity. This video encourages us to imagine ourselves moving to different areas in the concert hall to understand where different technologies interface. Once the concert ends, we talk about underlying neural mechanisms and technology that allow researchers and innovators to interact with the brain.
This module addresses how neurotechnology is currently used for medical and non-medical applications, and how it might advance in the future.
This module covers a brief history of the neurotechnology industry, bringing the history of brain-computer interfacing to life through engaging skits and stories.