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. Aberdeen 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.
The Berry Street Centre occupies a three-storey 1950s building, which has recently been refurbished to a high specification. ...
The Berry Street Centre occupies a three-storey 1950s building, which has recently been refurbished to a high specification. It is in a prominent and convenient location in the heart of Aberdeen's busy and thriving retail and business area and close to all amenities. The off-shore oil capital of Europe, Aberdeen is known for its outward looking, pioneering spirit. Over the last 30 years, the city has reinvented itself from a regional port dependent upon fishing, farming and tourism, to become the centre of the UK's energy industry and one of Europe's most enterprising regions. It boasts the second highest rate of business formation and the highest concentration of knowledge based businesses in Scotland and is a founding member of the World Energy Cities Partnership. Other important sectors in the city's economy include tourism and distribution, the public sector, financial services, manufacture, agriculture and food processing, IT and construction.
This instructor-led, live training in Aberdeen (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 Aberdeen (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 Aberdeen (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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