Overview This short course provides a practical introduction to building artificial neural networks using PyTorch, a powerful and flexible deep l earning framework. The course covers the fundamentals of PyTorch, including tensors, automatic differentiation, and model building.

This tutorial provides an introduction to deep learning using high performance computing. This workshop will cover accessing deep learning containers, resource allocation and helpful tools, how to choose a GPU, and deep learning slurm scripts.

This hands-on workshop provides an overview of neural networks with a focus on GPUs. Example codes will be provided in both Tensorflow and Pytorch and how to use them on Rivanna.

This tutorial provides a practical introduction to building artificial neural networks using PyTorch, a powerful and flexible deep learning framework. The course covers the fundamentals of PyTorch, including tensors, automatic differentiation, and model building.

This tutorial introduces the deep learning approach to computational drug discovery.

This hands-on workshop provides links to the MathWorks online courses in Data Science. It focuses on Machine Learning, Deep Learning, and Data Analytics

This hands-on tutorial will show you how to classify images with a pretrained neural network, modify a pretrained network to classify images into new specified classes, and build a neural network from scratch.