機械学習モデルをモバイル デバイスや IoT デバイスにデプロイします
TensorFlow Lite は、デバイス上での推論を可能にする、オープンソースのディープ ラーニング フレームワークです。
仕組み
TensorFlow Lite ユーザーのご紹介
The task of recovering a high resolution (HR) image from its low resolution counterpart is commonly referred to as Single Image Super Resolution (SISR). In this tutorial, we use a pre-trained ESRGAN model from TensorFlow Hub and generate super resolution images using...
We are excited to announce that Teachable Machine now allows you to train your own sound classification model and export it in the TensorFlow Lite (TFLite) format. Then you can integrate the TFLite model to your mobile applications or your IoT devices. This is an easy...
Learn how to train and deploy an ML model on an Android app in just a few lines of code with TensorFlow Lite Model Maker and Android Studio. From here you can then explore how to use various tools from Google to turn a prototype into a production app. Presented by...
Learn about the differences between ML on a supercomputer and ML on a portable device, and the tools and technologies that Google has developed to allow you to bring your work to mobile devices without reinventing the wheel. We'll cover the basics and also special...