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TensorFlow Lite for Embedded Linux

 21 時間
TensorFlow Lite is an open source deep learning framework for executing models on mobile and embedded devices with limited compute and memory resources. This instructor-led, live training (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 machine learning 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 their default capabilities.
  • Deploy deep learning models on embedded devices running Linux to solve physical world problems such as recognizing images and voice, predicting patterns, and initiating movements and responses from robots and other embedded systems in the field.
Format of the Course
  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.
Course Customization Options
  • To request a customized training for this course, please contact us to arrange.
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TensorFlow Lite for Android

 21 時間
TensorFlow Lite is an open source deep learning framework for mobile devices and embedded systems. This instructor-led, live training (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.
Format of the Course
  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.
Course Customization Options
  • To request a customized training for this course, please contact us to arrange.
  • To learn more about TensorFlow, please visit: https://www.tensorflow.org/lite/
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TensorFlow Lite for iOS

 21 時間
TensorFlow Lite is an open source deep learning framework for mobile devices and embedded systems. This instructor-led, live training (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.
Format of the Course
  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.
Course Customization Options
  • To request a customized training for this course, please contact us to arrange.
続きを読む...

Tensorflow Lite for Microcontrollers

 21 時間
TensorFlow Lite for Microcontrollers is a port of TensorFlow Lite designed to run machine learning models on microcontrollers and other devices with limited memory. This instructor-led, live training (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.
Format of the Course
  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.
Course Customization Options
  • To request a customized training for this course, please contact us to arrange.
続きを読む...

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