Learn how to deploy deep learning models on mobile and embedded devices with TensorFlow Lite. This course was developed by the TensorFlow team and Udacity as a practical approach to model deployment for software developers. You'll get hands-on experience with the TensorFlow Lite framework as you deploy deep learning models on Android, iOS, and even an embedded Linux platform. By the end of this course, you'll have all the skills necessary to start deploying your own deep learning models into your apps.
Overview
Syllabus
- Introduction to TensorFlow Lite
- Learn how TensorFlow works under the hood,Learn how to quantize models,Learn how to test your TF Lite Models in Python
- TensorFlow Lite on Android
- Deploy a TF Lite Model to an Android app that classifies images of cats and dogs,Deploy a TF Lite Model to an Android app that classifies images of various objects,Deploy a TF Lite Model to an Android app that performs object detection,Deploy a TF Lite Model to an Android app that recognizes speech commands
- TensorFlow Lite on Swift
- Deploy a TF Lite Model to an iOS app that classifies images of cats and dogs,Deploy a TF Lite Model to an iOS app that classifies images of various objects,Deploy a TF Lite Model to an iOS app that performs object detection,Deploy a TF Lite Model to an iOS app that recognizes speech commands
- TensorFlow Lite on IoT
- Deploy a TF Lite Model to a Linux embedded platform that classifies images of cats and dogs,Deploy a TF Lite Model to a Linux embedded platform that classifies images of various objects,Deploy a TF Lite Model to a Linux embedded platform that performs object detection
Taught by
Daniel Situnayake, Paige Bailey and Juan Delgado
