Free Course
Introduction to TensorFlow Lite
by
Learn how to deploy deep learning models on mobile and embedded devices with TensorFlow Lite.
Nanodegree Program
Deep Learning
Build Deep Learning Models Today
Build cutting-edge AI projects supported by dedicated mentors.
About this Course
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.
Course Cost
Free
Timeline
Approx. 2 months
Skill Level
intermediate
Included in Product
Rich Learning Content
Taught by Industry Pros
Interactive Quizzes
Self-Paced Learning
Join the Path to Greatness
This course is your first step towards a new career with the Deep Learning Nanodegree Program.
Free Course
Introduction to TensorFlow Lite
Learn how to deploy deep learning models into your apps using TensorFlow Lite.
Course Leads
Daniel Situnayake
Developer Advocate, Google
Paige Bailey
Developer Advocate, Google
Juan Delgado
Content Developer, Udacity
What You Will Learn
lesson 1
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
lesson 2
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
lesson 3
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
lesson 4
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
Prerequisites and Requirements
General Experience: Some familiarity with the TensorFlow Lite framework, and comfortability with Object Oriented Programming, Python, Swift, Android, and Machine Learning.
See the Technology Requirements for using Udacity.
Why Take This Course
With TensorFlow Lite, the Google TensorFlow team has introduced the next evolution of the TensorFlow Framework, specifically designed to enable machine learning at low latency on mobile and embedded devices. This course was created as a practical approach to model deployment for software developers, providing hands-on experience deploying deep learning models on Android, iOS, and even an embedded Linux platform. Get started today to stay on the cutting-edge of machine learning practices.