Technology Lab: Using AI Frameworks in Jupyter Notebook

Overview

Instructor: Zhenhua He

Time: Wednesday, June 2, 1:00PM-3:03PM

Location: Zoom session only

Prerequisites: Basic Python skills and account on HPRC systems

This short course contains a set of four sessions to help a new user start with his/her machine learning projects on supercomputers at the Texas A&M High Performance Research Computing.

Course Materials

Jupyter notebooks and sample data for AI Technology Lab is available below:

  • Technology lab (Summer 2021): 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

Agenda

There are totally 4 lab sessions

  • Lab 1 - Jupyter Notebook (15 mins)
  • We will set up a Python virtual environment and run JupyterLab on the HPRC Portal.

  • Lab 2 - Data Exploration (30 mins)
  • We will go through simple examples with two popular Python modules: Pandas and Matplotlib for simple data exploration.

  • Lab 3 - Machine Learning (30 minutes)
  • We will learn to use scikit-learn for linear regression and classification applications.

  • Lab 4 - Deep Learning (30 minutes)
  • We will learn how to use Keras to create and train a simple image classification model with deepneural networks (DNN)