Join Mark III Systems, NVIDIA, and Hewlett Packard Enterprise for a virtual AI Education Series in Fall 2021 for the University of Houston and HPE Data Science Institute communities.  This education series is open to all and will cover a cross section of Artificial Intelligence, Machine Learning, and Deep Learning, starting with basic practical tutorials, labs, ways to get started, and will also feature ways to accelerate and scale research via AI/ML and HPC.

AI/ML Education Series:

Thursday, Oct 21st (11am-12pm CT)

 

Intro to Computer Vision

Speaker: Michaela Buchanan, Data Scientist, Mark III

In this session, we'll cover the components of a Convolutional Neural Network (CNN) and talk about how they can be used to address image classification, object detection, and image segmentation use cases.  

We'll cap the session with a 20-minute rapid mini-workshop via Jupyter Notebook where we'll use code examples to build a CNN image classifier as well as using pretrained model libraries for object detection and image segmentation.

 

Previous Sessions/Replays:

Thursday, Sept 2nd (11am-12pm CT)

 

Intro to Machine Learning and AI:  What is it and why we do we need it?

Speaker: Michaela Buchanan, Data Scientist, Mark III

In this session, we’ll cover the basics around what Machine Learning is, look at the different ML techniques and methods, examine what a typical ML project lifecycle looks like, and discuss some of the most commonly used example algorithms.

This session will also include a 20-minute rapid mini-workshop via Jupyter Notebook where we'll use an example dataset from Kaggle and take it through the steps of training and evaluating a model to make predictions using ML.

 

Thursday, Sept 16th (11am-12pm CT)

 

Intro to Deep Learning: An introduction to neural networks

Speaker: Michaela Buchanan, Data Scientist, Mark III

In this session, we'll cover the basics around what Deep Learning is, look at how it fits within the AI/ML universe, dive into neural networks (including CNNs, LSTMs, and GANs), and walk through a typical Deep Learning project lifecycle.  

We'll cap the session with a 20-minute rapid mini-workshop via Jupyter Notebook where we'll use an example dataset (CIFAR-10) to train and evaluate a neural network model using Keras.

 

Wednesday, Oct 6th (11am-12pm CT)

 

Machine Learning Tools in the Social Sciences (at the HPE DSI)

Speaker: Sebastián Vallejo Vera, Ph.D., University of Houston & Johnny Miller, HPE

We are in an era of data abundance and machine-learning tools are increasingly used to extract meaning from all types of datasets.

In this quick demo, I will briefly showcase how social scientist can take advantage of machine-learning tools in classification tasks that ultimately help us take advantage of the current data availability.

I will provide a step-by-step tutorial on how to take advantage of the computation resources available at the HPE DSI using RoBERTa infrastructure in a text classification task. I will also provide examples of other Natural Language Processing tasks useful to social scientist.