Information Theory, Inference and Learning Algorithms

Information Theory, Inference and Learning Algorithms 下载 mobi epub pdf 电子书 2025


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David J. C. MacKay



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发表于2025-03-06

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Cambridge University Press 2003-10-6 Hardcover 9780521642989


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Sir David John Cameron MacKay FRS FInstP FICE (22 April 1967 – 14 April 2016) was a British physicist, mathematician, and academic. He was the Regius Professor of Engineering in the Department of Engineering at the University of Cambridge and from 2009 to 2014 was Chief Scientific Adviser to the UK Department of Energy and Climate Change (DECC). MacKay authored the book Sustainable Energy – Without the Hot Air.

Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.

Information Theory, Inference and Learning Algorithms 下载 mobi epub pdf txt 电子书 格式

Information Theory, Inference and Learning Algorithms mobi 下载 pdf 下载 pub 下载 txt 电子书 下载 2025

Information Theory, Inference and Learning Algorithms 下载 mobi pdf epub txt 电子书 格式 2025

Information Theory, Inference and Learning Algorithms 下载 mobi epub pdf 电子书
想要找书就要到 图书大百科
立刻按 ctrl+D收藏本页
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##(读过部分章节)与很多教材不同的是,把很多东西放在一起讨论,很有意思。 适合做个补充类读物。要是学信息论或者机器学习还是以其他教材为主吧

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##读了一点,组会解散了,于是没有继续下去了,感觉这书讲得好 detail 啊。 组会在读的书之一。 水木 AI 版有人推荐,有电子版,有时间看一下。看章节标题似乎很不错的样子。

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信息论和机器学习是一个硬币的两面。传统的信息论两条理论上的香农,工程应用是通信。具体的:贝叶斯数据模型,蒙特卡洛,变分法,聚类算法,神经网络。大脑是压缩和通信系统

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##可惜看过了,理解不深刻,又忘了。 准备拾起来,虽然基本上工作用不上,就当是完成一个念想吧! 加油!  

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Information Theory, Inference and Learning Algorithms mobi epub pdf txt 电子书 格式下载 2025


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