Submission information
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
Webform: Knowledge Base Resources
Approved: Yes
Title: AI/ML TechLab - Accelerating AI/ML Workflows on a Composable Cyberinfrastructure
Category: Docs
Skill Level:
Intermediate (305)
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:
- Presentation slides (https://hprc.tamu.edu/training/aces_ai_techlab.html)
- GitHub Repository of Examples and Hands-on Exercises (https://github.com/happidence1/AI-TechLab)
Tags:
ACES (789), documentation (746), TAMU (788), ai (271), visualization (781), deep-learning (303), machine-learning (272), neural-networks (435), login (682), authentication (695), composable-systems (666), gpu (80), nvidia (527), slurm (71), bash (242), modules (534), vim (480), anaconda (535), conda (227), programming (5), python (69), scikit-learn (273)
Domain:
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