Are you an engineer who wants to design intelligent computer vision systems that learn from complex or large-scale datasets? Would you like to build your visual AI development skills?
Get the hands-on knowledge you need to develop deep learning computer vision applications—both on embedded systems and in the cloud—with TensorFlow, today’s most popular framework for deep learning.
The class covers deep learning for computer vision applications using TensorFlow 2.0. We assume that:
To make sure you’re up to speed on Python, please review sections 1-5 of this online Python tutorial before class: https://docs.python.org/3/tutorial/.
The class is now online, so you can take it at your convenience! The class is a combination of lecture and lab exercises using Jupyter Notebooks. We cover the following topics:
When you sign up for this training, remember to also sign up for the Embedded Vision Summit. The Summit gives you access to hundreds of hours of additional learning. You’ll hear from 100+ presentations, see dozens of exhibitors and demos, and mingle online with over 1,000 fellow innovators building or enabling vision in their products.
At #EVS21? Stop by The @thekhronosgroup's kiosk! They're an open-industry consortium of hardware and software companies creating advanced, royalty-free, acceleration standards for 3D graphics, AR/VR, vision and machine learning, and you'll want to check them out.
If you're attending the #EVS21, make sure to stop by @Hacksterio's kiosk! They're an @Avnet community and the world’s largest developer community for learning, programming, and building hardware with 1.6M+ members and 27K+ open source projects.