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Intelligent Mobile Projects with TensorFlow

You're reading from   Intelligent Mobile Projects with TensorFlow Build 10+ Artificial Intelligence apps using TensorFlow Mobile and Lite for iOS, Android, and Raspberry Pi

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788834544
Length 404 pages
Edition 1st Edition
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Author (1):
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Jeff Tang Jeff Tang
Author Profile Icon Jeff Tang
Jeff Tang
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Table of Contents (14) Chapters Close

Preface 1. Getting Started with Mobile TensorFlow FREE CHAPTER 2. Classifying Images with Transfer Learning 3. Detecting Objects and Their Locations 4. Transforming Pictures with Amazing Art Styles 5. Understanding Simple Speech Commands 6. Describing Images in Natural Language 7. Recognizing Drawing with CNN and LSTM 8. Predicting Stock Price with RNN 9. Generating and Enhancing Images with GAN 10. Building an AlphaZero-like Mobile Game App 11. Using TensorFlow Lite and Core ML on Mobile 12. Developing TensorFlow Apps on Raspberry Pi 13. Other Books You May Enjoy

Training a simple commands recognition model

In this section, we'll summarize the steps used in the well-written TensorFlow Simple Audio Recognition tutorial (https://www.tensorflow.org/versions/master/tutorials/audio_recognition) and also add a few tips that can be of help to you while training the model.

The simple speech commands recognition model we'll build will be able to recognize 10 words: "yes," "no," "up," "down," "left," "right," "on," "off," "stop," and "go"; it can also detect silence. If it finds no silence and none of the 10 words, it'll generate "unknown." The speech commands dataset we'll download and use for training the model, when we run the tensorflow/example/speech_commands/train.py script later, actually contains 20 more words...

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