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Practical TensorFlow.js - Deep Learning in Web App Development (Paperback, 1st ed.) Loot Price: R1,327
Discovery Miles 13 270
You Save: R302 (19%)
Practical TensorFlow.js - Deep Learning in Web App Development (Paperback, 1st ed.): Juan De Dios Santos Rivera

Practical TensorFlow.js - Deep Learning in Web App Development (Paperback, 1st ed.)

Juan De Dios Santos Rivera

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List price R1,629 Loot Price R1,327 Discovery Miles 13 270 | Repayment Terms: R124 pm x 12* You Save R302 (19%)

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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.

General

Imprint: Apress
Country of origin: United States
Release date: September 2020
First published: 2020
Authors: Juan De Dios Santos Rivera
Dimensions: 235 x 155 x 24mm (L x W x T)
Format: Paperback
Pages: 303
Edition: 1st ed.
ISBN-13: 978-1-4842-6272-6
Categories: Books > Computing & IT > Computer hardware & operating systems > Handheld devices (eg Palm, PocketPC)
Books > Computing & IT > Computer programming > General
Books > Computing & IT > Internet > Internet languages > General
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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LSN: 1-4842-6272-7
Barcode: 9781484262726

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