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:
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 set up a Python virtual environment 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)