| 書目名稱 | Practical TensorFlow.js | | 副標題 | Deep Learning in Web | | 編輯 | Juan De Dios Santos Rivera | | 視頻video | http://file.papertrans.cn/754/753301/753301.mp4 | | 概述 | 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 c | | 圖書封面 |  | | 描述 | 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 | | 出版日期 | Book 2020 | | 關(guān)鍵詞 | TensorFlow; js; TensorFlow; JavaScript; Artificial Intelligence; Computer Science; Machine Learning; Deep L | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4842-6273-3 | | isbn_softcover | 978-1-4842-6272-6 | | isbn_ebook | 978-1-4842-6273-3 | | copyright | Juan De Dios Santos Rivera 2020 |
The information of publication is updating
|
|
|Archiver|手機版|小黑屋|
派博傳思國際
( 京公網(wǎng)安備110108008328)
GMT+8, 2025-10-20 22:38
發(fā)表于 2025-3-21 18:07:18
