Introduction To TensorFlow Lite | FREE Course

Organization Name : Udacity

Details

COURSE COST : Free

TIMELINE : Approx. 2 Months

SKILL LEVEL : Intermediate

Included In Product

• Rich Learning ContentRich Learning Content
• Interactive QuizzesInteractive Quizzes
• Taught by Industry ProsTaught by Industry Pros
• Self-Paced LearningSelf-Paced Learning

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.

What You’ll 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.

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.

WHAT DO I GET?
Instructor videos
Learn by doing exercises
Taught by industry professionals

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