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. Brighton 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.
NobleProg -- Your Local Training Provider
Brighton
3rd Floor, Queensberry House , Brighton, united kingdom, BN1 3XF
This centre occupies a prominent location on Queens Road which links Brighton station to the Churchill Square shopping cen...
This centre occupies a prominent location on Queens Road which links Brighton station to the Churchill Square shopping centre and the seafront. Queensberry House, which offers some sea views, is in the heart of the business district in this city. Brighton is a highly sophisticated and modern resort with a thriving economy and tourist industry. Millions of visitors flock here every year, both for leisure and to attend conferences and exhibitions at the Brighton Centre, one of the largest multi-purpose conference and exhibition centres in the country. Because it is home to so many businesses involved in media, particularly digital or 'new media', Brighton is sometimes referred to as 'Silicon Beach'. The city's priority sectors, which include financial services, creative industries and environmental technologies as well as digital media, are all growing steadily.
This instructor-led, live training in Brighton (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 Brighton (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 Brighton (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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