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Deep Learning with JavaScript
US $43.93
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Brand New
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eBay item number:364635957554
Item specifics
- Condition
- Book Title
- Deep Learning with JavaScript
- Narrative Type
- book
- ISBN
- 9781617296178
- Subject Area
- Mathematics, Computers
- Publication Name
- Deep Learning with Javascript
- Publisher
- Manning Publications Co. LLC
- Item Length
- 9.3 in
- Subject
- Intelligence (Ai) & Semantics, Neural Networks, General, Programming Languages / Javascript
- Publication Year
- 2020
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Item Height
- 1.2 in
- Item Weight
- 34.5 Oz
- Item Width
- 7.5 in
- Number of Pages
- 350 Pages
About this product
Product Identifiers
Publisher
Manning Publications Co. LLC
ISBN-10
1617296171
ISBN-13
9781617296178
eBay Product ID (ePID)
12038422045
Product Key Features
Number of Pages
350 Pages
Publication Name
Deep Learning with Javascript
Language
English
Publication Year
2020
Subject
Intelligence (Ai) & Semantics, Neural Networks, General, Programming Languages / Javascript
Type
Textbook
Subject Area
Mathematics, Computers
Format
Trade Paperback
Dimensions
Item Height
1.2 in
Item Weight
34.5 Oz
Item Length
9.3 in
Item Width
7.5 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
2020-288474
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
006.3/1
Synopsis
Deep learning has transformed the fields of computer vision, image processing, and natural language applications. Thanks to TensorFlow.js, now JavaScript developers can build deep learning apps without relying on Python or R. Deep Learning with JavaScript shows developers how they can bring DL technology to the web. Written by the main authors of the TensorFlow library, this new book provides fascinating use cases and in-depth instruction for deep learning apps in JavaScript in your browser or on Node. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications., Running deep learning applications in the browser or on Node-based backends opens up exciting possibilities for smart web applications. With the TensorFlow.js library, you build and train deep learning models with JavaScript. Offering uncompromising production-quality scalability, modularity, and responsiveness, TensorFlow.js really shines for its portability. Its models run anywhere JavaScript runs, pushing ML farther up the application stack. In Deep Learning WITH JavaScript, you'll learn to use TensorFlow.js to build deep learning models that run directly in the browser. This fast-paced book, written by Google engineers, is practical, engaging, and easy to follow. Through diverse examples featuring text analysis, speech processing, image recognition, and self-learning game AI, you'll master all the basics of deep learning and explore advanced concepts, like retraining existing models for transfer learning and image generation. What's Inside Image and language processing in the browser, Tuning ML models with client-side data, Text and image creation with generative deep learning, Source code samples to test, and modify For JavaScript programmers interested in deep learning. Book jacket., Deep learning has transformed the fields of computer vision, image processing, and natural language applications. Thanks to TensorFlow.js, now JavaScript developers can build deep learning apps without relying on Python or R. Deep Learning with JavaScript shows developers how they can bring DL technology to the web. Written by the main authors of the TensorFlow library, this new book provides fascinating use cases and in-depth instruction for deep learning apps in JavaScript in your browser or on Node. Deploying computer vision, audio, and natural language processing in the browser Fine-tuning machine learning models with client-side data Constructing and training a neural network Interactive AI for browser games using deep reinforcement learning Generative neural networks to generate music and pictures TensorFlow.js is an open-source JavaScript library for defining, training, and deploying deep learning models to the web browser. It's quickly gaining popularity with developers for its amazing set of benefits including scalability, responsiveness, modularity, and portability. Shanging Cai and Eric Nielsen are senior software engineers on the Google Brain team. Stan Bileschi is the technical lead for Google's TensorFlow Usability team, which built the TensorFlow Layers API. All three have advanced degrees from MIT. Together, they're responsible for writing most of TensorFlow.js.
LC Classification Number
QA76.73.J39C34 2020
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