Learning Deep Architectures for AI pdf epub mobi txt 電子書 下載 2024


Learning Deep Architectures for AI

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Yoshua Bengio
136
695.00 元
散裝
9781601982940

圖書標籤: 深度學習  機器學習  人工智能  神經網絡  AI  計算機  計算機科學  programming   


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发表于2024-11-22

Learning Deep Architectures for AI epub 下載 mobi 下載 pdf 下載 txt 電子書 下載 2024

Learning Deep Architectures for AI epub 下載 mobi 下載 pdf 下載 txt 電子書 下載 2024

Learning Deep Architectures for AI pdf epub mobi txt 電子書 下載 2024



圖書描述

Theoretical results suggest that in order to learn the kind of complicated

functions that can represent high-level abstractions (e.g., in

vision, language, and other AI-level tasks), one may need deep architectures.

Deep architectures are composed of multiple levels of non-linear

operations, such as in neural nets with many hidden layers or in complicated

propositional formulae re-using many sub-formulae. Searching

the parameter space of deep architectures is a difficult task, but learning

algorithms such as those for Deep Belief Networks have recently been

proposed to tackle this problem with notable success, beating the stateof-

the-art in certain areas. This monograph discusses the motivations

and principles regarding learning algorithms for deep architectures, in

particular those exploiting as building blocks unsupervised learning of

single-layer models such as Restricted Boltzmann Machines, used to

construct deeper models such as Deep Belief Networks.

Learning Deep Architectures for AI 下載 mobi epub pdf txt 電子書

著者簡介


圖書目錄


Learning Deep Architectures for AI pdf epub mobi txt 電子書 下載
想要找書就要到 小哈圖書下載中心
立刻按 ctrl+D收藏本頁
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用戶評價

評分

棄瞭

評分

棄瞭

評分

相見恨晚。把Hinton的papers翻瞭個遍,沒想到在這本書上纔讓我對RBM的認識最深刻。

評分

RBM開始實在跟不上瞭,棄…前麵的intuition挺有意思的…

評分

看得懵懵懂懂

讀後感

評分

具体内容: More precisely ,functions that can be compactly represented by a depth k architecture might require an exponential number of computational elements to be represented by a depth k-1 architecture. 这句意思是k-1层架构可以表示的函数需要的计算元素...

評分

具体内容: More precisely ,functions that can be compactly represented by a depth k architecture might require an exponential number of computational elements to be represented by a depth k-1 architecture. 这句意思是k-1层架构可以表示的函数需要的计算元素...

評分

讲的比较清晰,提供了关键的数学计算内容,作为综述来看是很不错的选择。但是不亲自推一遍细节很难透彻理解,需要一些机器学习、随机过程、信息论和最优化理论的知识。理论框架介绍的很清楚,有助于理解目前各类变种。  

評分

讲的比较清晰,提供了关键的数学计算内容,作为综述来看是很不错的选择。但是不亲自推一遍细节很难透彻理解,需要一些机器学习、随机过程、信息论和最优化理论的知识。理论框架介绍的很清楚,有助于理解目前各类变种。  

評分

具体内容: More precisely ,functions that can be compactly represented by a depth k architecture might require an exponential number of computational elements to be represented by a depth k-1 architecture. 这句意思是k-1层架构可以表示的函数需要的计算元素...

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