Online or onsite, instructor-led live TensorFlow Lite training courses demonstrate through interactive hands-on practice how to use TensorFlow Lite to to deploy deep learning models on embedded devices.
TensorFlow Lite training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Sharjah onsite live TensorFlow Lite trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
TensorFlow Lite is also known as Google's TensorFlow Lite.
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Sharjah Expo Centre
Al Taawun Street, Al Khan, United Arab Emirates, P.O.Box 3222
Located in the United Arab Emirates (UAE), Expo Centre Sharjah naturally commands a strategic position at the heart of the re...
Located in the United Arab Emirates (UAE), Expo Centre Sharjah naturally commands a strategic position at the heart of the region’s business and commercial hub. As a stable and dynamic country, the UAE is an established gateway to the Middle East and beyond into the CIS region, North Africa and the Indian Subcontinent.
This is one of the newest Expo centres in the UAE. Adjacent to the Corniche with convenient connections to the E11, the UAE’s longest road, it’s a strategic location with excellent links to Dubai and the airport. This centre's location is ideal for companies with international clients, and for those that value convenience, accessibility and practicality. Within walking distance, there is an abundance of restaurants and cafes to explore and enjoy outside of work. Close by, you can also find Sharjah Aquarium
This instructor-led, live training in Sharjah (online or onsite) is aimed at developers who wish to use TensorFlow Lite to deploy deep learning models on embedded devices.
By the end of this training, participants will be able to:
Install and configure Tensorflow Lite on an embedded device.
Understand the concepts and components underlying TensorFlow Lite.
Convert existing models to TensorFlow Lite format for execution on embedded devices.
Work within the limitations of small devices and TensorFlow Lite, while learning how to expand the scope of operations that can be run.
Deploy a deep learning model on an embedded device running Linux.
This instructor-led, live training in Sharjah (online or onsite) is aimed at developers who wish to use TensorFlow Lite to develop mobile applications with deep learning capabilities.
By the end of this training, participants will be able to:
Install and configure TensorFlow Lite.
Understand the principles behind TensorFlow, machine learning and deep learning.
Load TensorFlow Models onto an Android device.
Enable deep learning and machine learning functionality such as computer vision and natural language recognition in a mobile application.
This instructor-led, live training in Sharjah (online or onsite) is aimed at engineers who wish to write, load and run machine learning models on very small embedded devices.
By the end of this training, participants will be able to:
Install TensorFlow Lite.
Load machine learning models onto an embedded device to enable it to detect speech, classify images, etc.
Add AI to hardware devices without relying on network connectivity.
This instructor-led, live training in (online or onsite) is aimed at developers who wish to use TensorFlow Lite to develop iOS mobile applications with deep learning capabilities.
By the end of this training, participants will be able to:
Install and configure TensorFlow Lite.
Understand the principles behind TensorFlow and machine learning on mobile devices.
Load TensorFlow Models onto an iOS device.
Run an iOS application capable of detecting and classifying an object captured through the device's camera.
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