In this session, we'll cover what datasets for Machine Learning and Deep Learning projects look like and how to find them. This will include highlighting some of the most popular datasets in the community today as well as good sources to download these datasets from. Some brief tips and tricks for cleaning up datasets will be covered and we'll conclude the session with a mini-workshop and lab showing how to import and interact with datasets in a Jupyter Notebook for a public health use case.

Kraft Heinz scientists will be discussing their partnering opportunity on Halo and answering questions directly from researchers. You can review the opportunity in advance here.

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 also include a Jupyter Notebook lab that will take attendees through the process of finetuning a simple LLM model for a sample disease diagnosis use case.

This session will cover the ML/DL ecosystem of container-powered technologies and the best ways to get started and accelerate your journey in building, training, deploying, and scaling your models, with the NVIDIA ecosystem software stack. We'll touch on NVIDIA NGC, Docker, Kubernetes, Singularity, and other ways to get started and get going quickly. In addition, this session will cover an overview on how to get started working with OSU HPC Services, if you need an HPC/AI cluster to train, deploy, and inference with larger models.

In this session, we'll cover the basics around NVIDIA's Omniverse platform for 3D Design Collaboration and Simulation and the ecosystem of building Digital Twins. We'll touch on not only how to set up and rollout an Omniverse environment, but also how to integrate frameworks, like Modulus (physics simulations) and Isaac (robotics) into Omniverse to visualize your models and research. Whether your work is focused on Engineering, Climate, Biomed, Robotics, Architecture, Natural Sciences, Computer Science, Business, or Data Science, we'll have something for you in this session.