Python shen du xue xi ru men : cong ling gou jian CNN he RNN = Deep learning from scratch /
Python深度学习入门 : 从零构建CNN和RNN = Deep learning from scratch /
Detailed summary in vernacular field.
Call Number: | Libro Electrónico |
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Main Author: | |
Other Authors: | |
Format: | Electronic eBook |
Language: | Chino Inglés |
Published: |
Beijing Shi :
Ren min you dian chu ban she,
2021.
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Edition: | Di 1 ban. |
Series: | Tu ling cheng xu she ji cong shu.
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Subjects: | |
Online Access: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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003 | OCoLC | ||
005 | 20231017213018.0 | ||
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082 | 0 | 4 | |a 005.13/3 |2 23 |
049 | |a UAMI | ||
100 | 1 | |a Weidman, Seth, |e author. | |
240 | 1 | 0 | |a Deep learning from scratch. |l Chinese |
245 | 1 | 0 | |6 880-01 |a Python shen du xue xi ru men : |b cong ling gou jian CNN he RNN = Deep learning from scratch / |c Saisi Weideman zhu Zheng Tianmin yi. |
246 | 3 | 1 | |a Deep learning from scratch |
250 | |6 880-02 |a Di 1 ban. | ||
264 | 1 | |6 880-03 |a Beijing Shi : |b Ren min you dian chu ban she, |c 2021. | |
300 | |a 1 online resource (214 pages) : |b illustrations. | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
490 | 1 | |6 880-04 |a Tu ling cheng xu she ji cong shu | |
504 | |a Includes bibliographical references | ||
520 | |6 880-05 |a Detailed summary in vernacular field. | ||
590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
650 | 0 | |a Python (Computer program language) | |
650 | 0 | |a Machine learning. | |
650 | 0 | |a Neural networks (Computer science) | |
650 | 0 | |a Artificial intelligence. | |
650 | 2 | |a Neural Networks, Computer | |
650 | 2 | |a Artificial Intelligence | |
650 | 2 | |a Machine Learning | |
650 | 6 | |a Python (Langage de programmation) | |
650 | 6 | |a Apprentissage automatique. | |
650 | 6 | |a Réseaux neuronaux (Informatique) | |
650 | 6 | |a Intelligence artificielle. | |
650 | 7 | |a artificial intelligence. |2 aat | |
650 | 7 | |a Artificial intelligence |2 fast | |
650 | 7 | |a Machine learning |2 fast | |
650 | 7 | |a Neural networks (Computer science) |2 fast | |
650 | 7 | |a Python (Computer program language) |2 fast | |
700 | 1 | |6 880-06 |a Zheng, Tianim, |e translator. | |
830 | 0 | |6 880-07 |a Tu ling cheng xu she ji cong shu. | |
856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9787115555649/?ar |z Texto completo (Requiere registro previo con correo institucional) |
880 | 1 | 0 | |6 245-01/$1 |a Python深度学习入门 : |b 从零构建CNN和RNN = Deep learning from scratch / |c 塞思·韦德曼著 ; 郑天民 译. |
880 | |6 250-02/$1 |a 第1版. | ||
880 | 1 | |6 264-03/$1 |a 北京市 : |b 人民邮电出版社, |c 2021. | |
880 | 1 | |6 490-04/$1 |a 图灵程序设计丛书 | |
880 | |6 520-05/$1 |a 深度学习技术的发展如火如荼,这些知识正迅速成为机器学习从业者甚至许多软件开发工程师的"加分项"。深度学习是一个立体的领域,仅从数学层面或代码层面学习,难免以偏概全,无法融会贯通。 本书作者认为,理解深度学习和神经网络需要多种思维模型。因此,本书从数学、示意图、Python代码三个维度帮助你立体地理解每一个概念,带你领略深度学习领域的全貌,从内到外地理解构建神经网络的每一步。你将学到以下内容。 为理解深度学习的概念和原理构建多种思维模型。 掌握嵌套函数、链式法则等数学概念。 掌握学习率衰减、权重初始化、dropout等优化技巧。 从零构建CNN和RNN等常见的神经网络架构。 使用PyTorch实现神经网络。. | ||
880 | 1 | |6 700-06/$1 |a 郑天民, |e translator. | |
880 | 0 | |6 830-07/$1 |a 图灵程序设计丛书. | |
994 | |a 92 |b IZTAP |