My Account Log in

1 option

Building mobile applications with TensorFlow / Pete Warden.

O'Reilly Online Learning: Academic/Public Library Edition Available online

View online
Format:
Book
Author/Creator:
Warden, Pete, author.
Language:
English
Subjects (All):
TensorFlow (Electronic resource).
Application software--Development.
Application software.
Mobile computing.
Physical Description:
1 online resource (1 volume) : illustrations
Edition:
First edition.
Place of Publication:
Sebastopol, CA : O'Reilly Media, [2017]
System Details:
text file
Summary:
Deep learning is an incredibly powerful technology for understanding messy data from the real world—and the TensorFlow machine learning library is the ideal way to harness that power. In this practical report, author Pete Warden, tech lead on the Mobile/Embedded TensorFlow team, demonstrates how to successfully integrate a Tensorflow deep-learning model into your Android and iOS mobile applications. Aimed specifically at developers who already have a TensorFlow model successfully working in a desktop environment, this report shows you through hands-on examples how to deploy mobile AI applications that are small, fast, and easy to build. You’ll explore use cases for on-device deep learning—such as speech, image, and object recognition—and learn how to deliver interactive applications that complement cloud services. With this report, you’ll explore: Use cases including speech, image, and object recognition, translation, and text classification Common patterns for integrating a deep-learning model into your application Several examples for running TensorFlow on Android, iOS, and Raspberry Pi Techniques for testing your deep-learning model inside your application Methods to help you prepare your solution for mobile deployment Optimizing your model for latency, RAM usage, model file size, and binary size
Notes:
Description based on online resource; title from title page (Safari, viewed January 14, 2019).
Includes bibliographical references.
ISBN:
9781491988435
1491988436
9781491988428
1491988428
OCLC:
1082522894

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

Find

Home Release notes

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Find catalog Using Articles+ Using your account