Deep Learning

Deep Learning pdf epub mobi txt 电子书 下载 2025

Ian Goodfellow is Research Scientist at OpenAI. Yoshua Bengio is Professor of Computer Science at the Université de Montréal. Aaron Courville is Assistant Professor of Computer Science at the Université de Montréal.

出版者:The MIT Press
作者:Ian Goodfellow
出品人:
页数:800
译者:
出版时间:2016-11-11
价格:USD 72.00
装帧:Hardcover
isbn号码:9780262035613
丛书系列:Adaptive Computation and Machine Learning
图书标签:
  • 深度学习 
  • 机器学习 
  • DeepLearning 
  • 人工智能 
  • AI 
  • MachineLearning 
  • 计算机 
  • 计算机科学 
  •  
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"Written by three experts in the field, Deep Learning is the only comprehensive book on the subject." -- Elon Musk, co-chair of OpenAI; co-founder and CEO of Tesla and SpaceX

Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.

The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.

Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

具体描述

读后感

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终于磕磕绊绊读完了,是我读的最纠结的书,总结一下感受。 第一个是书里面的推导真心不知道是给谁看的,有的时候很简单的步骤写上去然后跳跃几个比较难的步骤,基本没法跟下去。 第二个是逻辑不太通顺,这可能和翻译有关系,再就是缺乏必要的背景介绍,内容之间的连接比较少。...  

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标准的国内高校出书,拉几个学生翻译,自己改一改就出版了。这个翻译真的是直译,比机翻好一些,有的语序都是英文原版的,看的非常费劲。内容方面倒是还行,相对来说比较容易入门。更推荐机械工业出版社的《神经网络与机器学习》这本书,在数学和公式推导方面更清楚,讲的也比...  

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1、推荐了很多书籍,关乎如何提升学习力 2、其中重大的方法就是远离社交网络,对此方法如下:1.完全脱离网络2.一周或一月设置几天或几周深度学习;不接触网络3.一天之中,设计可使用网络的时间4.一天置之中规划每一分钟 3、深入学习可以提升生产力:在一段时间内全然投入到一件...  

用户评价

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好多地方看不懂。有些章节感觉讲的不如维基百科和某些博客讲的清楚

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目前学习深度学习的必读书目了

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他们起草的时候指出他们一些公式错误,所以上面有我的名字,哈哈

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三个星期读完了第一遍,有很多切入角度不错,有很多地方看不懂,需要读论文,抽空再刷一遍

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读的中文版:https://github.com/exacity/deeplearningbook-chinese 第三部分还没读下去,深觉数学不够 含金量台高,7,8,11三章真是调参的人森经验了

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