This tutorial will cover basic machine learning techniques, such as Linear Regression, Decision Tree, Support Vector Machine, Naive Bayes, K- Nearest Neighbors, K-Means, and Random Forest, using TensorFlow on HAL system.
NCSA is organizing training sessions throughout the Spring 2020 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. To sign up for training, just request a HAL account prior to the training session and mention "spring training" when describing how the system will be used in your project.
In conjunction with these training sessions, we are holding walk-in consultation hours for HAL users. These consultations will be provided by Benjamin Rabe and Ke Xu on Mondays, Tuesdays, Thursdays and Fridays 3:00-5:00pm in 1104 NCSA. No prior registration is required.
NCSA is also organizing two hackathons during the Spring 2020 semester to engage students and staff in AI problem solving. There will be two-hour tutorials prior to each hackathon to train entrants on the HAL compute clusters that will be used for running hackathon code. The hackathons will be full-day events, the hackathon projects and signup details will be provided later.