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 Madrid or in NobleProg corporate training centers in Madrid.
TensorFlow Lite is also known as Google's TensorFlow Lite.
NobleProg -- Your Local Training Provider
Madrid - Chamartín Business Area
NobleProg Madrid, Street Bausá 27, Madrid, spain, 28033
Madrid is a municipality and city of Spain is the most populated city of the country, with 3 165 235 inhabitants. On the econ...
Madrid is a municipality and city of Spain is the most populated city of the country, with 3 165 235 inhabitants. On the economic level, it is the fourth richest city in Europe, after London, Paris and Moscow. It is an influential cultural center and has museums of international reference, among which stand out the Prado Museum, the National Museum of Art Reina Sofia, Thyssen-Bornemisza and CaixaForum Madrid.
Being one of the largest cities in all of Spain and one of the most populated, it is characterized by having an extensive transport network consisting of rail, metro and bus lines, in addition to its airport.
Located in the business area of Chanmartin five minutes from Plaza Castilla and less than ten minutes from the airport Madrid Barajas and Madrid downtown area.
This instructor-led, live training in Madrid (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 Madrid (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 (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.
This instructor-led, live training in Madrid (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.
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