MARC details
| 000 -CABECERA |
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| campo de control de longitud fija |
04074 a2200313 4500 |
| 008 - DATOS DE LONGITUD FIJA--INFORMACIÓN GENERAL |
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| campo de control de longitud fija |
2020 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781617296178 |
| 040 ## - FUENTE DE CATALOGACIÓN |
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| Centro catalogador/agencia de origen |
GAMADERO |
| Lengua de catalogación |
spa |
| Centro/agencia transcriptor |
GAMADERO |
| 041 ## - CÓDIGO DE IDIOMA |
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| Código de lengua del texto/banda sonora o título independiente |
Inglés |
| 050 00 - SIGNATURA TOPOGRÁFICA DE LA BIBLIOTECA DEL CONGRESO |
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| Número de clasificación |
QA76.73J39 2022 |
| 100 ## - ENTRADA PRINCIPAL--NOMBRE DE PERSONA |
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| Nombre de persona |
SHANGING CAI |
| 245 ## - MENCIÓN DEL TÍTULO |
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| Título |
DEEP LEARNING WITH JAVA SCRIPT / |
| 250 ## - MENCION DE EDICION |
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| Mención de edición |
1RA |
| 260 ## - PUBLICACIÓN, DISTRIBUCIÓN, ETC. |
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| Nombre del editor, distribuidor, etc. |
MANNING |
| Lugar de publicación, distribución, etc. |
UNITED STATES OF AMERICA |
| Fecha de publicación, distribución, etc. |
2020 |
| 300 ## - DESCRIPCIÓN FÍSICA |
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| Extensión |
533 |
| Otras características físicas |
ILUSTRACION |
| Dimensiones |
19 X 23.5 CM |
| 504 ## - NOTA DE BIBLIOGRAFÍA, ETC. |
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| Nota de bibliografía, etc. |
ISBN: 9781617296178<br/>Publisher: Manning Publications<br/>Imprint: Manning Publications<br/>Pub date: 21 Jan 2020<br/>DEWEY: 006.31<br/>DEWEY edition: 23<br/>Language: English<br/>Number of pages: 350<br/>Weight: 978g<br/>Height: 235mm<br/>Width: 187mm<br/>Spine width: 30mm |
| 505 ## - NOTA DE CONTENIDO CON FORMATO |
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| Nota de contenido con formato |
PART 1 - MOTIVATION AND BASIC CONCEPTS<br/><br/>1 • Deep learning and JavaScript<br/><br/>PART 2 - A GENTLE INTRODUCTION TO TENSORFLOW.JS<br/><br/>2 • Getting started: Simple linear regression in TensorFlow.js<br/><br/>3 • Adding nonlinearity: Beyond weighted sums<br/><br/>4 • Recognizing images and sounds using convnets<br/><br/>5 • Transfer learning: Reusing pretrained neural networks<br/><br/>PART 3 - ADVANCED DEEP LEARNING WITH TENSORFLOW.JS<br/><br/>6 • Working with data<br/><br/>7 • Visualizing data and models<br/><br/>8 • Underfitting, overfitting, and the universal workflow of machine learning<br/><br/>9 • Deep learning for sequences and text<br/><br/>10 • Generative deep learning<br/><br/>11 • Basics of deep reinforcement learning<br/><br/>PART 4 - SUMMARY AND CLOSING WORDS<br/><br/>12 • Testing, optimizing, and deploying models<br/><br/>13 • Summary, conclusions, and beyond |
| 520 ## - RESUMEN, ETC. |
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| Resumen, etc. |
Summary<br/><br/>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.<br/><br/>Foreword by Nikhil Thorat and Daniel Smilkov.<br/><br/>About the technology<br/><br/>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.<br/><br/>About the book<br/><br/>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.<br/><br/>What's inside<br/><br/>- Image and language processing in the browser<br/>- Tuning ML models with client-side data<br/>- Text and image creation with generative deep learning<br/>- Source code samples to test and modify<br/><br/>About the reader<br/><br/>For JavaScript programmers interested in deep learning.<br/><br/>About the author<br/><br/>Shanging Cai, Stanley Bileschi and Eric D. Nielsen are software engineers with experience on the Google Brain team, and were crucial to the development of the high-level API of TensorFlow.js. This book is based in part on the classic, Deep Learning with Python by François Chollet.<br/> |
| 526 ## - NOTA DE INFORMACIÓN SOBRE EL PROGRAMA DE ESTUDIO |
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| Program name |
Ingeniería en Tecnologías de la Información y Comunicación |
| 650 #0 - PUNTO DE ACCESO ADICIONAL DE MATERIA--TÉRMINO DE MATERIA |
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| Término de materia o nombre geográfico como elemento de entrada |
PROGRAMACION |
| 9 (RLIN) |
971 |
| 700 ## - ENTRADA AGREGADA--NOMBRE PERSONAL |
|---|
| Nombre de persona |
STANLEY BILESCHI |
| 700 ## - ENTRADA AGREGADA--NOMBRE PERSONAL |
|---|
| Nombre de persona |
ERIC D. NIELSEN |
| 700 ## - ENTRADA AGREGADA--NOMBRE PERSONAL |
|---|
| Nombre de persona |
F |
| 942 ## - ELEMENTOS DE ENTRADA SECUNDARIOS (KOHA) |
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| Tipo de ítem Koha |
Libro |
| Fuente del sistema de clasificación o colocación |
Clasificación Decimal Dewey |
| Edición |
1RA |
| Parte de la signatura que corresponde a la clasificación (Parte de la clasificación) |
QA76.73J39 |
| 945 ## - CATALOGADORES |
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| Número del Creador del Registro |
1 |
| Nombre del Creador del Registro |
admin |
| Número de último modificador del registro |
1260 |
| Nombre del último modificador del registro |
Norma Gabriela Corona Arreguin |
