Fundamentals of Deep Learning Online Workshop
Fundamentals of Deep Learning Online Workshop
The NVIDIA Deep Learning Institute (DLI) and the University of Florida invite CIGR members to attend a Fundamentals of Deep Learning Online Workshop. This two half day workshop will be conducted on January 24th and 26th, 2022, from 8:00 AM to 12:00 NOON (New York Time zone). This workshop is exclusively for verifiable academic students, staff, and researchers. To ensure that you benefit form this workshop please see the prerequisites below.
About This Workshop:
NVIDIA
DLI offers hands-on training for developers, data scientists, and
researchers looking to solve challenging problems with deep learning
and accelerated computing.
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.
Businesses worldwide are using artificial intelligence 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.
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 will 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.
About the Instructor:
Dr. Matt Gitzendanner’s background is in plant evolutionary genetics and genomics where he uses genetic tools to study the conservation, evolution, and diversity of plants. The field is generally computationally intensive, and Matt has worked for 10 years training users how to use HiPerGator and other high-performance computing systems to do the amazing research that is done across the University of Florida campus. Matt is an NVIDIA DLI Certified Instructor and a University of Florida Ambassador.
Workshop Agenda:
|
Day 1: Monday, January 24, 2022,
8:00 AM to 12:00 NOON (ETD) |
|
|
Introduction |
§ Meet the instructor. § Create an account at courses.nvidia.com/join |
|
The Mechanics of Deep
Learning |
Explore the fundamental mechanics and tools involved in successfully training deep neural networks: § Train your first computer vision model to learn the process of training. § Introduce convolutional neural networks to improve accuracy of predictions in vision applications. § Apply data augmentation to enhance a dataset and improve model generalization. |
|
Break (10 mins) |
|
|
Pre-trained Models and
Recurrent Networks |
Leverage pre-trained models to solve deep learning challenges quickly. Train recurrent neural networks on sequential data: § Integrate a pre-trained image classification model to create an automatic doggy door. § Leverage transfer learning to create a personalized doggy door that only lets in your dog. § Train a model to autocomplete text based on New York Times headlines. |
|
Day 1 Wrap up (35 mins) |
|
| Day 2: Wednesday, January 26, 2022, 8:00 AM to 12:00 NOON (ETD) | |
|
Final Project: Object
Classification |
Apply computer vision to create a model that distinguishes between fresh and rotten fruit: § Create and train a model that interprets color images. § Build a data generator to make the most out of small datasets. § Improve training speed by combining transfer learning and feature extraction. § Discuss advanced neural network architectures and recent areas of research where students can further improve their skills. |
|
Final Review |
§ Review key learnings and answer questions. § Complete the assessment and earn a certificate. § Complete the workshop survey. § Learn how to set up your own AI application development environment. |
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.
This workshop is brought to you courtesy of:
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