         Tensorflow Lite for Microcontrollers培训

Introduction

Microcontroller vs Microprocessor
Microcontrollers designed for machine learning tasks
Overview of TensorFlow Lite Features

On-device machine learning inference
Solving network latency
Solving power constraints
Preserving privacy
Constraints of a Microcontroller

Energy consumption and size
Processing power, memory, and storage
Limited operations
Getting Started

Preparing the development environment
Running a simple Hello World on the Microcontroller
Creating an Audio Detection System

Obtaining a TensorFlow Model
Converting the Model to a TensorFlow Lite FlatBuffer
Serializing the Code

Converting the FlatBuffer to a C byte array
Working with Microcontroller'ss C++ Libraries

Coding the microcontroller
Collecting data
Running inference on the controller
Verifying the Results

Running a unit test to see the end-to-end workflow
Creating an Image Detection System

Classifying physical objects from image data
Creating TensorFlow model from scratch
Deploying an AI-enabled Device

Running inference on a microcontroller in the field
Troubleshooting

Summary and Conclusion