NVIDIA, Dell, Mark III, and the Clemson-MUSC AI Hub would like to host an AI/Machine Learning Education Series for institutions in South Carolina and the greater community in Fall 2024. This education series is 100% virtual and will include both tutorials and virtual "rapid labs" for attendees delivered via Jupyter Notebook. There will be a series of sessions that will feature industry experts in Machine Learning, who will dive into current trends around AI/ML. We hope you can join us!
AI/ML Education Series:
Wednesday, Jan 8th (3pm-4pm ET)
MONAI for AI and Medical Imaging
Speaker: Data Scientist, Mark III
MONAI is an open source project and set of collaborative frameworks built on top of PyTorch designed to accelerate research and clinical collaboration around Medical Imaging.
Frameworks include MONAI Label, Core, and Deploy, and enables image labeling and learning, data integrations and extensions, training via PyTorch, and the deployment and operation of models built using MONAI. We'll cap this session with a lab that will utilize MONAI to label and train on a dataset of sample medical images.
Replays (Past Sessions):
Wednesday, Nov 6th (3pm-4pmET)
Introduction to Machine Learning and AI: What is it and why we do we need it?
Speaker: 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. Specifically the use case will cover using quantitative data to predict benign and malignant tumors, based on a large dataset.
Wednesday, Dec 4th (3pm-4pm ET)
Intro to Large Language Models (LLMs)
Speaker: Data Scientist, Mark III
In this session, we'll overview the landscape around LLMs and Generative AI and look into a few of the most popular frameworks for training and using LLM models, including Mosaic MPT, Falcon, and Nemo. This session will include a Jupyter Notebook lab that will take attendees through the process of training and finetuning a simple LLM model.