Practical TensorFlow.js

Deep Learning in Web App Development

Autoren: Rivera, Juan

Vorschau
  • Focus less on deep learning concepts, and the functionalities of the framework, and more on actual applications using JavaScript 
  • Work with a wide range of algorithms, methods, and use cases, such as convolutional neural networks, object detection, image translation, and linear regression
  • Build a real and deployed deep learning product using JavaScript and TensorFlow.js
Weitere Vorteile

Dieses Buch kaufen

eBook 26,99 €
Preis für Deutschland (Brutto)
  • ISBN 978-1-4842-6273-3
  • Versehen mit digitalem Wasserzeichen, DRM-frei
  • Erhältliche Formate: PDF, EPUB
  • Sofortiger eBook Download nach Kauf und auf allen Endgeräten nutzbar
  • Mengenrabatt verfügbar
Softcover 37,44 €
Preis für Deutschland (Brutto)
Über dieses Buch

Develop and deploy deep learning web apps using the TensorFlow.js library. TensorFlow.​js​ is part of a bigger framework named TensorFlow, which has many tools that supplement it, such as TensorBoard​, ​ml5js​, ​tfjs-vis. This book will cover all these technologies and show they integrate with TensorFlow.​js​ to create intelligent web apps.
The most common and accessible platform users interact with everyday is their web browser, making it an ideal environment to deploy AI systems. TensorFlow.js is a well-known and battle-tested library for creating browser solutions. Working in JavaScript, the so-called language of the web, directly on a browser, you can develop and serve deep learning applications.You'll work with deep learning algorithms such as feedforward neural networks, convolutional neural networks (CNN), recurrent neural networks (RNN), and generative adversarial network (GAN). Through hands-on examples, apply these networks in use cases related to image classification, natural language processing, object detection, dimensionality reduction, image translation, transfer learning, and time series analysis.

Also, these topics are very varied in terms of the kind of data they use, their output, and the training phase. Not everything in machine learning is deep networks, there is also what some call shallow or traditional machine learning. While TensorFlow.js is not the most common place to implement these, you'll be introduce them and review the basics of machine learning through TensorFlow.js.
What You'll Learn

  • Build deep learning products suitable for web browsers
  • Work with deep learning algorithms such as feedforward neural networks, convolutional neural networks (CNN), recurrent neural networks (RNN), and generative adversarial network (GAN)
  • Develop apps using image classification, natural language processing, object detection, dimensionality reduction, image translation, transfer learning, and time series analysis
Who This Book Is For

Programmers developing deep learning solutions for the web and those who want to learn TensorFlow.js with at least minimal programming and software development knowledge. No prior JavaScript knowledge is required, but familiarity with it is helpful.

Über die Autor*innen

Juan De Dios Santos Rivera is a machine learning engineer who focuses on building data-driven and machine learning-driven platforms. As a Big Data Software Engineer for mobile apps, his role has been to build solutions to detect spammers and avoid the proliferation of them. This book goes hand-to-hand with that role in building data solutions. As the AI field keeps growing, developers need to keep extending the reach of our products to every platform out there, which includes web browsers.

Inhaltsverzeichnis (11 Kapitel)

Inhaltsverzeichnis (11 Kapitel)

Dieses Buch kaufen

eBook 26,99 €
Preis für Deutschland (Brutto)
  • ISBN 978-1-4842-6273-3
  • Versehen mit digitalem Wasserzeichen, DRM-frei
  • Erhältliche Formate: PDF, EPUB
  • Sofortiger eBook Download nach Kauf und auf allen Endgeräten nutzbar
  • Mengenrabatt verfügbar
Softcover 37,44 €
Preis für Deutschland (Brutto)
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Bibliografische Information

Bibliographic Information
Buchtitel
Practical TensorFlow.js
Buchuntertitel
Deep Learning in Web App Development
Autoren
Copyright
2020
Verlag
Apress
Copyright Inhaber
Juan De Dios Santos Rivera
eBook ISBN
978-1-4842-6273-3
DOI
10.1007/978-1-4842-6273-3
Softcover ISBN
978-1-4842-6272-6
Auflage
1
Seitenzahl
XXIV, 303
Anzahl der Bilder
67 schwarz-weiß Abbildungen
Themen