Information Theory, Inference and Learning Algorithms pdf epub mobi txt 电子书 下载 2026
- 机器学习
- 信息论
- 人工智能
- 计算机
- 数学
- AI
- Inference
- 计算机科学
- Information Theory
- Inference
- Learning Algorithms
- Machine Learning
- Statistics
- Data Science
- Algorithms
- Probability
- Deep Learning
- Coding
具体描述
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.
作者简介
目录信息
读后感
1.刚从图书馆借到这本书，顺着书中的支持网站，发现作者把公开课视频也免费放到网上了，还可以直接下到英文原版电子版，这是什么精神~ ”A series of sixteen lectures covering the core of the book "Information Theory, Inference, and Learning Algorithms (Cambridge Un...
评分1.刚从图书馆借到这本书，顺着书中的支持网站，发现作者把公开课视频也免费放到网上了，还可以直接下到英文原版电子版，这是什么精神~ ”A series of sixteen lectures covering the core of the book "Information Theory, Inference, and Learning Algorithms (Cambridge Un...
评分学习信息论的时候，老师推荐的，然后就买来了。实例很多，习题也很经典，花费了一个学期看了一遍，感觉对信息论的理解完全高了好多个层次。
评分学习信息论的时候，老师推荐的，然后就买来了。实例很多，习题也很经典，花费了一个学期看了一遍，感觉对信息论的理解完全高了好多个层次。
评分Mackay在我心中是一个多才多艺的天才，他重新发现了LDPC码的价值，使得这一具有革命性影响的信道码没有沉没在故纸堆中。这本书神奇地把数据压缩、通信理论、神经网络甚至是分布式算法这些我们在多门课程中学习的东西统一到了统计尤其是Bayesian统计的大框架下来，使得我们的...
用户评价
“ this exciting textbook”....才知道MacKay去世了，可惜啊。
评分I only read it a little
评分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
评分早年读的，当时的感觉是深入但不浅出。适合做参考，作主打可能会事倍功半。
评分好书！只看了信息论部分，深入浅出
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