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Virtual Workshop (Offered by NVIDIA): Fundamentals of Deep Learning

Instructor: Sri Koundinyan, NVIDIA
When: October 24th, 9:00 am – 4:30 pm CST (8 hours)
Format: Virtual (in-person at the 2nd OAK conference in Little Rock, AR)
Where: Zoom
Who: Open to faculty, researchers, post-doc and graduate students from Oklahoma, Arkansas and Kansas region.

Number of seats: 50
Cost: Free ($0)


**If you already registered for the in-person meeting as part of your OAK conference registration, you do not need to use this form.**



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 shopping experiences. 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 language translation. 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 processing. 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.


Learning Objectives:
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 model architectures
  • Enhance datasets through data augmentation to improve model accuracy
  • 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



Registration is now closed.



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