TensorFlow Lite培訓

TensorFlow Lite培訓

在線或現場由講師指導的實時 TensorFlow Lite 培訓課程通過交互式實踐演示如何使用 TensorFlow Lite 在嵌入式設備上部署深度學習模型。 TensorFlow Lite 培訓可作為“在線實時培訓”或“現場實時培訓”。在線實時培訓(又名“遠程實時培訓”)是通過交互式遠程桌面進行的。現場實時培訓可以在 台灣 中的客戶場所本地進行,也可以在 台灣 中的 NobleProg 公司培訓中心進行。 TensorFlow Lite 也稱為 Google 的 TensorFlow Lite。 NobleProg——您當地的培訓提供商

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TensorFlow Lite課程大綱

課程名稱
課程時長
概覽
課程名稱
課程時長
概覽
21小時
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.
21小時
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/
21小時
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.
21小時
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.

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