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. Onsite live TensorFlow Lite training can be carried out locally on customer premises in Exeter or in NobleProg corporate training centers in Exeter.
TensorFlow Lite is also known as Google's TensorFlow Lite.
NobleProg -- Your Local Training Provider
Exeter
The Senate, Southernhay Gardens, Exeter, united kingdom, EX1 1UG
The business centre is located in Exeter, with excellent transport links that is served by two mainline train stations, Exete...
The business centre is located in Exeter, with excellent transport links that is served by two mainline train stations, Exeter Central and Exeter St Davids, which provide regular rail services to all major UK cities. Exeter has been identified by as one of the top 10 most profitable business locations and the county of Devon is regularly voted as number one in England for quality of life.
The Senate is the finest office building in Exeter and offers the largest available floors. This exceptional grade A building is adjacent to the city’s new Crown Court and only a short stroll from the vibrant heart of the city centre, with its bars, restaurants and recently completed Princesshay shopping centre.
The building provides over 72,000 sqft of high specification office accommodation over 5 floors and incorporates underground secure parking for 72 cars. As you would expect from a building of this calibre, the specification and finish reflect a commitment to the highest standards. Efficient space management is expressed in the flexibility of the floorplates, which can be tailored to the needs of each occupier.
This instructor-led, live training in Exeter (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 Exeter (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 Exeter (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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