AI/ML TechLab - Accelerating AI/ML Workflows on a Composable Cyberinfrastructure

Submission Number: 277
Submission ID: 4157
Submission UUID: 5b136f58-a649-45c2-87ab-91a53641735b
Submission URI: /form/resource

Created: Mon, 10/09/2023 - 11:37
Completed: Mon, 10/09/2023 - 11:43
Changed: Sun, 12/03/2023 - 20:51

Remote IP address: 165.91.13.137
Submitted by: Zhenhua He
Language: English

Is draft: No
Approved Yes
Title AI/ML TechLab - Accelerating AI/ML Workflows on a Composable Cyberinfrastructure
Category Docs
Skill Level Intermediate
Description This technology lab contains a set of sessions to help a new user start an AI project on the ACES cluster, a composable accelerator testbed at Texas A&M University. You will learn how to create and activate a virtual environment, manipulate and visualize data with Pandas and Matplotlib, use Scikit-learn for linear regression and classification applications, and use Pytorch to create and train a simple image classification model with deep neural networks (DNN).
Link to Resource
Tags ACES, documentation, TAMU, ai, visualization, deep-learning, machine-learning, neural-networks, login, authentication, composable-systems, gpu, nvidia, slurm, bash, modules, vim, anaconda, conda, programming, python, scikit-learn
Domain
Would you like to associate this resource with an Affinity Group?