Introduction to Generative Models
| Event Date: | February 22, 2024 |
|---|---|
| Hosted By: | Graduate Research Information Portal |
| Time: | 3:00 - 4:30 PM |
| Location: | Virtual |
| Contact Name: | Office of Graduate Professional Development |
| Contact Email: | profdev@purdue.edu |
| Priority: | No |
| School or Program: | Graduate Program |
| College Calendar: | Show |
This workshop will provide an introduction to the world of generative models in machine learning. We start by defining what generative models are and how they differ from traditional predictive models. Key concepts like probability distribution and latent space representation will be covered, setting the foundation for understanding how these models learn to generate new data.
The session will highlight various types of generative models, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and more, with practical sessions on how to implement and train some of these models. Participants will gain insights into the applications of these models in fields such as image generation, natural language processing, and synthetic data creation. We will also discuss the ethical considerations and challenges of using generative models. This workshop is perfect for those who are curious about the creative and innovative aspects of machine learning. Note: Some familiarity with basic machine learning concepts and programming (ideally in Python) is recommended for attendees.
Register HERE