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Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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Practical TensorFlow.js - Deep Learning in Web App Development (Paperback, 1st ed.)
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Practical TensorFlow.js - Deep Learning in Web App Development (Paperback, 1st ed.)
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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.
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