AI at the Edge
(Jetson TX2, Jetson Nano and CORAL)
Postponed until Further Notice
NUST, H-12, Islamabad
Overview of Ai at the Edge
This workshop will cover deep learning for deploying AI and computer vision on Jetson TX2 and Jetson Nano. Participants will get a stronger background in deep learning, will be able to load and run a pre-trained deep neural network on the devices and learn how to retrain the network with your own dataset to produce a live demo. Moreover, this workshop is designed to provide industry-level experience in developing embedded systems projects using the widely used ARM architecture. Arm AI enables a new era of ultraefficient machine learning inference, delivering scalable AI and neural network functionality at any point on the performance curve.
WHY AI AT THE EDGE
Learning Outcomes
Overview of Deep Learning Domain
Challenges in deploying Deep Learning Models on Edge Devices
Edge device landscape - Holistic overview
Hands-on experience with Jetson Devices (TX2 and Nano) and CORAL
Decision Making w.r.t platform selection for Real Life Deployment
Topics of the Workshop include, but are not limited to
- Compression of neural networks for inference deployment
- Learning on edge devices, including federated and continuous learning
- Understanding the difficulties and opportunities using common ML frameworks
- Applications and experiences from deployed use cases requiring embedded ML
- New benchmarks suited to edge devices and learning on the edge scenarios
We Will Provide
All the boards required in the commencement of this workshop will be provided by AI Lounge. The accessories such as micro SD card, HDMI cable, Jumper, Barrel Jack power supply will be provided.
GPU Access
Accessories
Lecture Slides
Jetson Nano, Jetson TX2 and CORAL
Dataset
Important
Pre Requisites for the Workshop Participants
- Python – Pytorch
- Basic understanding of Deep learning models
- GPU programming (CUDA Programming)
- Basic concept of deploying a normal DNN on GPU
- Basic background in computer architecture like pipelining, caching, instruction-set, assembly programming (for advanced workshops on FPGA)
- Differential Calculus
- Optional: HDL Programming experience in Verilog or VHDL
Featured Trainers & Speakers
Four renowned professors and practitioners in the field of Artificial Intelligence, including Prof. Dr. Faisal Shafait, Director Deep Learning Laboratory, NCAI, Dr. Rehan Ahmed who has several years of experience in this field, Prof. Dr. Muhammad Shafique, a Professor in New York University, Abu Dhabi and Dr. Hassan Aqeel Khan, CEO of AI Lounge will lead the workshop.
Dr. Rehan Ahmed
Assistant Professor, NUST
Prof. Dr. Faisal Shafait
Director, Deep Learning Lab, NCAI
Dr. Hassan Aqeel Khan
Assistant Professor, University of Jeddah – KSA
Prof. Dr. Muhammad Shafique
Professor, New York University, Abu Dhabi
WHY AI AT THE EDGE
What’s More!
Lunch and Tea
Lunch and Tea during the workshop will be provided by AI Lounge
Certificates
Varified Certificates will be provided by AI Lounge to all the workshop participants.
Duration
The duration of this workshop will be five consecutive days, with eight hour session each day.
PARTNERS