Technology Lab: Using AI Frameworks in Jupyter Notebook

Overview

Instructor: Zhenhua He

Time: Friday, March 11, 1:30PM-4:00PM

Location: Blocker 220

Prerequisites: Current HPRC account, Basic Python

This technology lab 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. You will learn how to create a virtual environment and install different libraries, 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 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

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)