Practical TensorFlow.js - Juan De Dios Santos Rivera - E-Book
SONDERANGEBOT

Practical TensorFlow.js E-Book

Juan De Dios Santos Rivera

0,0
66,99 €
Niedrigster Preis in 30 Tagen: 52,99 €

-100%
Sammeln Sie Punkte in unserem Gutscheinprogramm und kaufen Sie E-Books und Hörbücher mit bis zu 100% Rabatt.

Mehr erfahren.
Beschreibung

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.

Das E-Book können Sie in einer beliebigen App lesen, die das folgende Format unterstützt:

PDF

Veröffentlichungsjahr: 2020

Bewertungen
0,0
0
0
0
0
0
Mehr Informationen
Mehr Informationen
Legimi prüft nicht, ob Rezensionen von Nutzern stammen, die den betreffenden Titel tatsächlich gekauft oder gelesen/gehört haben. Wir entfernen aber gefälschte Rezensionen.