Brief Introduction
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.Course Summary
Learn the basics of TensorFlow Lite, a lightweight machine learning framework that enables on-device inference with low latency and a small binary size. This course covers the fundamentals of TensorFlow Lite and shows you how to build and deploy models on mobile and embedded devices.Key Learning Points
- Understand the basics of TensorFlow Lite and its differences from TensorFlow
- Learn how to convert TensorFlow models to TensorFlow Lite models
- Deploy models on mobile and embedded devices with TensorFlow Lite
Job Positions & Salaries of people who have taken this course might have
- USA: $112,000
- India: ₹1,900,000
- Spain: €41,000
- USA: $112,000
- India: ₹1,900,000
- Spain: €41,000
- USA: $97,000
- India: ₹900,000
- Spain: €29,000
- USA: $112,000
- India: ₹1,900,000
- Spain: €41,000
- USA: $97,000
- India: ₹900,000
- Spain: €29,000
- USA: $87,000
- India: ₹800,000
- Spain: €25,000
Related Topics for further study
- TensorFlow Lite
- Machine Learning on Mobile Devices
- On-Device Inference
- Model Deployment
- Embedded Systems
Learning Outcomes
- Understand how to use TensorFlow Lite for on-device inference
- Convert TensorFlow models to TensorFlow Lite models
- Deploy TensorFlow Lite models on mobile and embedded devices
Prerequisites or good to have knowledge before taking this course
- Familiarity with TensorFlow
- Knowledge of machine learning basics
Course Difficulty Level
IntermediateCourse Format
- Self-paced
- Online
- Video-based
Similar Courses
- TensorFlow Developer Certificate
- Mobile Web Specialist Certification
Related Education Paths
Notable People in This Field
- Andrew Ng
- Jeff Dean
Related Books
Description
Learn how to deploy deep learning models on mobile and embedded devices with TensorFlow Lite.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.
Knowledge
- Instructor videosLearn by doing exercisesTaught by industry professionals
Outline
- 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
Summary of User Reviews
Learn the basics of TensorFlow Lite with this comprehensive course on Udacity. Students praise the course for its clear explanations and engaging content.Key Aspect Users Liked About This Course
Clear explanationsPros from User Reviews
- Engaging content
- Good pacing
- Hands-on exercises
- Responsive instructors
Cons from User Reviews
- Some technical difficulties
- Lack of advanced topics
- Not suitable for experienced users
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