Hands-on TensorFlow Lite for Intelligent Mobile Apps

Apply Machine Learning models in real-time in mobile devices with the new and powerful TensorFlow Lite

This complete guide will teach you how to build and deploy Machine Learning models on your mobile device with TensorFlow Lite. You will understand the core architecture of TensorFlow Lite and the inbuilt models that have been optimized for mobiles.

You will learn to implement smart data-intensive behavior, fast, predictive algorithms, and efficient networking capabilities with TensorFlow Lite. You will master the TensorFlow Lite Converter, which converts models to the TensorFlow Lite file format. This course will teach you how to solve real-life problems related to Artificial Intelligence—such as image, text, and voice recognition—by developing models in TensorFlow to make your applications really smart. You will understand what Machine Learning can do for you and your mobile applications in the most efficient way. With the capabilities of TensorFlow Lite you will learn to improve the performance of your mobile application and make it smart.

By the end of the course, you will have learned to implement AI in your mobile applications with TensorFlow.

The code bundle for this video course is available at https://github.com/PacktPublishing/Hands-on-Tensorflow-Lite-for-Intelligent-Mobile-Apps

Style and Approach
You will gain an insight into solving real-life problems through Deep Learning using TensorFlow as the main tool for building models that will be later deployed on a mobile device. This course starts with a theoretical introduction and reinforces every concept by a practical code implementation. After a first simplistic example is used to understand the basics, different real-life problems in Computer Vision will deepen your knowledge by walking you through classical steps in developing an app such as identifying challenges, tackling problems, and deploying our ideas.

What You Will Learn
Learn basic Deep Learning concepts
Build Deep Learning models in TensorFlow
Understand the main components of a TensorFlow model
Debug and improve TensorFlow models
Deploy TensorFlow models on iOS and Android platforms
Design solutions to real-life computer vision problems
Tackle typical challenges when developing real-life applications

Table of Contents
INTRODUCTION TO DEEP LEARNING
DEVELOPING OUR FIRST TENSORFLOW MODEL
HANDWRITING RECOGNITION APP
PATTERN RECOGNITION APP
GESTURE RECOGNITION APP
VOICE RECOGNITION APP

Download rapidgator
https://rg.to/file/dd972b6e53595da58b9f05f271bce2b8/pkt_HandsonTensorFlowLiteIntelligentMobileApps.part1.rar.html
https://rg.to/file/3d69456e852593bafc162bd5be2eeec2/pkt_HandsonTensorFlowLiteIntelligentMobileApps.part2.rar.html

Download nitroflare
http://nitroflare.com/view/E6540910FAFDB53/pkt_HandsonTensorFlowLiteIntelligentMobileApps.part1.rar
http://nitroflare.com/view/B58E5E17F5D2595/pkt_HandsonTensorFlowLiteIntelligentMobileApps.part2.rar

Download 百度云

你是VIP 1个月(1 month)赞助会员，