NCSA organized online training sessions throughout the Fall 2022 semester to help users to get started with deep learning projects on HAL. These sessions are designed for novice users to learn about the system and start building deep neural network models. Watch all of our training sessions below!
FAll 2022 session videos
GETTING STARTED WITH HAL
Overview: This tutorial will introduce new users to HAL system, how to interact with it through Open OnDemand web interface, including Jupiter notebook and VS Code, and through command line interface via SSH. The tutorial will cover the Anaconda environment, batch job submission, data transfer, as well as an overview to the basic machine learning workflow.
- Training Slides
- Instructor: Volodymyr Kindratenko, Director of the Center for Artificial Intelligence Innovation
- Date: September 7, 2022
Introduction to Machine Learning and Neural Networks
Overview: This tutorial will provide an easy to follow introduction to machine learning with neural networks. We will go over various examples from simple dense networks to convolutional network architectures using TensorFlow framework on HAL system.
- GitHub Notebook
- Instructor: Aaron Saxton, Data Engineer, NCSA
- Date: September 14, 2022
Introduction to TensorFlow
Overview: This tutorial will introduce basics of TensorFlow necessary to build a neural network, train it and evaluate the accuracy of the model.
- Training Instructions
- GitHub Repository Notebook
- Instructor: Shirui Luo, Research Scientist, NCSA
- Date: September 21, 2022
Introduction to PyTorch
Overview: This tutorial will introduce basics of PyTorch framework necessary to build a neural network, train it and evaluate the accuracy of the model.
- Training Notebook
- Instructor: Priyam Mazumdar, Graduate Student, NCSA
- Date: September 28, 2022
Data Loading and Tools in PyTorch and TensorFlow
Overview: This tutorial will demonstrate how to use data loaders provided with PyTorch and TensorFlow and how to develop application-specific data loaders. Other topics will include how to make use of different tools, such as Weight&Biases, to help with model development and training.
Instructor: William Eustis, Undergraduate Student, NCSA
Date: October 5, 2022
HOW TO USE PRE-TRAINED MODELS
Overview: There are several popular AI model repositories that provide access to pre-trained models via easy-to-use APIs. Hugging Face is one of the latest such repositories that hosts a number of very recent models, such as Facebook’s OPT and OpenAI’s GPT models, as well as many datasets. This tutorial will show how to use basic pre-trained PyTorch models and then will introduce how to get started with using models from the Hugging Face ecosystem.
Instructor: Priyam Mazumdar, NCSA Grad Student Researcher
Date: November 16, 2022