WORKSHOP: Fundamentals of Deep Learning (offered by NVIDIA)
Wed June 7 8:30am-5:30pm @ Oklahoma State U
Contact: [log in to unmask]
Workshop (Offered by NVIDIA): Fundamentals of Deep Learning
Instructor: Sri Koundinyan, NVIDIA
When: June 7th, 8:30 am – 5:30 pm
(8 hours with 1-hour lunch; food will be provided)
Format: Hybrid format.
In-person (limited to 45 participants)
and Virtual (via Zoom).
OSU attendees should register as in-person attendees,
as preference will be given to non-OSU participants for
the virtual participation.
Where: 002 General Academic Building, Oklahoma State
University-Stillwater and Zoom
Who: Open to faculty, researchers, post-doc and graduate
students from Oklahoma, Arkansas and Kansas region.
Cost: Free ($0)
Businesses worldwide are using artificial intelligence (AI) to
solve their greatest challenges.
Healthcare professionals use AI to enable more accurate,
faster diagnoses in patients.
Retail businesses use it to offer personalized customer
Automakers use it to make personal vehicles, shared mobility,
and delivery services safer and more efficient.
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
Using deep learning, computers can learn and recognize
patterns from data that are considered too complex or subtle
for expert-written software.
In this workshop, you'll learn how deep learning works through
hands-on exercises in computer vision and natural language
You'll train deep learning models from scratch, learning tools
and tricks to achieve highly accurate results.
You'll also learn to leverage freely available,
state-of-the-art pre-trained models to save time and get
your deep learning application up and running quickly.
By participating in this workshop, you'll:
* Learn the fundamental techniques and tools required to
train a deep learning model
* Gain experience with common deep learning data types and
* Enhance datasets through data augmentation to improve
* Leverage transfer learning between models to achieve
efficient results with less data and computation
* Build confidence to take on your own project with a modern
deep learning framework
For in-person attendees, a Windows PC will be provided
at site, but laptops are permitted.
Registration (Closes May 31st):
The in-person session is currently full.
For a chance to attend in-person, select the option to be
added to the waitlist.
Final availability will be determined closer to the workshop
date; registrants beyond the 45 person capacity will be sent
a link to participate virtually.
For questions, please email:
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