Learning Deep Architectures for AI 在线电子书 图书标签: 深度学习 机器学习 人工智能 神经网络 AI 计算机 计算机科学 programming
发表于2024-11-21
Learning Deep Architectures for AI 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024
相见恨晚。把Hinton的papers翻了个遍,没想到在这本书上才让我对RBM的认识最深刻。
评分RBM开始实在跟不上了,弃…前面的intuition挺有意思的…
评分RBM开始实在跟不上了,弃…前面的intuition挺有意思的…
评分RBM开始实在跟不上了,弃…前面的intuition挺有意思的…
评分看得懵懵懂懂
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.
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。
评分讲的比较清晰,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。
评分具体内容: 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...
评分讲的比较清晰,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。
评分讲的比较清晰,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。
Learning Deep Architectures for AI 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024