Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning) pdf epub mobi txt 电子书 下载 2024


Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)

简体网页||繁体网页
Carl Edward Rasmussen
The MIT Press
2005-12-01
244
USD 36.00
Hardcover
Adaptive Computation and Machine Learning
9780262182539

图书标签: 机器学习  GaussianProcess  高斯过程  MachineLearning  统计学习  Gaussian  ML  人工智能   


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发表于2024-12-23

Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning) epub 下载 mobi 下载 pdf 下载 txt 电子书 下载 2024

Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning) epub 下载 mobi 下载 pdf 下载 txt 电子书 下载 2024

Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning) pdf epub mobi txt 电子书 下载 2024



图书描述

Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics.The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes.

Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning) 下载 mobi epub pdf txt 电子书

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Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning) pdf epub mobi txt 电子书 下载
想要找书就要到 小哈图书下载中心
立刻按 ctrl+D收藏本页
你会得到大惊喜!!

用户评价

评分

易读(从machine learning)角度。深度不够(从数学角度)

评分

have a go with it if you are really interested in predicting the unknown.=]Need any examples? well, your longevity,stock market,weather forecast.....countless really..=P

评分

因为科研要用看了一半 这辈子都不会忘记GPR了...

评分

只读了regression那章

评分

最好的GP教材

读后感

评分

内容不多,毕竟只有薄薄一本,有一定的实际参考价值,是一本还可以的入门书籍。 如果本身对于Kernel的方法以及统计的学习方法有一定的理解的话,看这个会觉得有些简单了。 和Bishop的书相比,内容和语言上,个人觉得还有一定的差距。

评分

内容不多,毕竟只有薄薄一本,有一定的实际参考价值,是一本还可以的入门书籍。 如果本身对于Kernel的方法以及统计的学习方法有一定的理解的话,看这个会觉得有些简单了。 和Bishop的书相比,内容和语言上,个人觉得还有一定的差距。

评分

内容不多,毕竟只有薄薄一本,有一定的实际参考价值,是一本还可以的入门书籍。 如果本身对于Kernel的方法以及统计的学习方法有一定的理解的话,看这个会觉得有些简单了。 和Bishop的书相比,内容和语言上,个人觉得还有一定的差距。

评分

内容不多,毕竟只有薄薄一本,有一定的实际参考价值,是一本还可以的入门书籍。 如果本身对于Kernel的方法以及统计的学习方法有一定的理解的话,看这个会觉得有些简单了。 和Bishop的书相比,内容和语言上,个人觉得还有一定的差距。

评分

内容不多,毕竟只有薄薄一本,有一定的实际参考价值,是一本还可以的入门书籍。 如果本身对于Kernel的方法以及统计的学习方法有一定的理解的话,看这个会觉得有些简单了。 和Bishop的书相比,内容和语言上,个人觉得还有一定的差距。

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Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning) pdf epub mobi txt 电子书 下载 2024


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