Fundamentals of Deep Learning (Part 2 of 3)
This three-part workshop will introduce deep learning techniques and applications.
Deep learning is a powerful AI approach that uses multi-layered artificial neural networks to deliver state-of-the-art accuracy in tasks such as object detection, speech recognition, and language translation. Using deep learning, computers can learn and recognize patterns from data that are considered too complex or subtle for expert-written software.
The second session will use pre-trained models and deep learning models to solve problems.
- The third session (Oct 2) focuses on object classification and research applications.
Important
This is the second session of a three-part course. Register for the series through session 1.
A laptop is required to participate. Students can borrow a laptop through the library’s Tech Lending program.
Prerequisites:
- An understanding of fundamental programming concepts in Python 3, such as functions, loops, dictionaries, and arrays; familiarity with Pandas data structures; and an understanding of how to compute a regression line. Suggested materials to satisfy prerequisites: Python Beginner’s Guide.
- Completion of Session 1 held on Sept 18
- Date:
- Wednesday, September 25, 2024 Show more dates
- Time:
- 1:00pm - 3:00pm
- Location:
- The Catalyst (Parks 199)
- Audience:
- Faculty Grad students & postdocs Undergrads
- Categories:
- Workshop > The Catalyst
Office hours will be held for this class on Wednesday September 18, 25, and Oct 2, 3-4 pm.
This workshop is part of a collaboration between Transitional AI Center (TrAC) and University Library to bring classes from the NVIDIA Deep Learning Institute to Iowa State. Questions about the program can be sent to trac@iastate.edu