Welcome to our TensorFlow Edge Tutorials section! Here you can find a range of tutorials that cover various aspects of using TensorFlow Edge, a framework designed to run machine learning models on edge devices.

Tutorials Overview

  • Basic Setup: Learn how to get started with TensorFlow Edge, including setting up the necessary environment and running the first model.
  • Model Deployment: Discover how to deploy models to edge devices, optimizing them for low power consumption and fast execution.
  • Custom Model Development: Understand the process of developing and optimizing custom models for edge deployment.
  • Integration with IoT: Explore how to integrate TensorFlow Edge with IoT devices and systems.

Getting Started

To begin, you'll need to set up your development environment. This includes installing TensorFlow Edge, setting up an edge device, and connecting to a server where you can download models.

Install TensorFlow Edge

Example Tutorial

Introduction to TensorFlow Lite

TensorFlow Lite is a lightweight solution for deploying TensorFlow models on edge devices. It is optimized for low-powered and high-performance applications.

What You'll Learn:

  • The basics of TensorFlow Lite
  • How to convert TensorFlow models to TensorFlow Lite
  • How to run TensorFlow Lite models on edge devices

Steps:

  1. Understand TensorFlow Lite: Read our guide on What is TensorFlow Lite?
  2. Convert Models: Learn how to convert models to TensorFlow Lite format using the TensorFlow Lite Converter.
  3. Run Models on Edge: Get instructions on running your TensorFlow Lite models on your edge device.

Start the TensorFlow Lite Tutorial

Additional Resources

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By following our tutorials, you'll gain a comprehensive understanding of TensorFlow Edge and its capabilities. Happy learning!