ACES: Technology Lab: Using AI Frameworks in Jupyter Notebook
Overview
Instructor: Zhenhua He
Time: Tuesday, November 29, 2022 10:00AM-12:30PM CT
Location: Zoom session
Prerequisites: Active HPRC account, basic Python
This technology lab contains a set of four sessions to help a new user start with machine learning projects on ACES and FASTER supercomputers at the Texas A&M High Performance Research Computing. You will learn how to load modules with jupyter lmod extension, manipulate and visualize data with Pandas and Matplotlib, use Scikit-learn for linear regression and classification applications and use Keras to create and train a simple image classification model with deep neural networks (DNN).
Course Materials
Jupyter notebooks and sample data for AI Technology Lab is available below:
- Technology lab (Spring 2024): PDF
- Technology lab (Fall 2022): PDF
- Lab 1 - Jupyter Notebook: Notebook
- Lab 2 - Data Exploration: Notebook
- Lab 3 - Machine Learning: Notebook
- Lab 4 - Deep Learning: Notebook
- Jupyter Notebook Cheat Sheet: PDF
- GitHub Repository for AI Tech Labs: Link
- Technology lab (Spring 2022): PDF
Agenda
There are totally 4 lab sessions
- Lab 1 - Jupyter Notebook (15 mins)
- Lab 2 - Data Exploration (30 mins)
- Lab 3 - Machine Learning (30 minutes)
- Lab 4 - Deep Learning (30 minutes)
We will load required modules with Jupyter Lmod extension and run JupyterLab on the HPRC Portal.
We will go through simple examples with two popular Python modules: Pandas and Matplotlib for simple data exploration.
We will learn to use scikit-learn for linear regression and classification applications.
We will learn how to use Keras to create and train a simple image classification model with deepneural networks (DNN)