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

简体网页||繁体网页

☆☆☆☆☆

出版者:Cambridge University Press

作者:David J. C. MacKay

出品人:

页数:640

译者:

出版时间:2003-10-6

价格:USD 80.00

装帧:Hardcover

isbn号码:9780521642989

丛书系列:

图书标签:

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

下载链接在页面底部

facebook linkedin mastodon messenger pinterest reddit telegram twitter viber vkontakte whatsapp 复制链接

想要找书就要到小美书屋

book.quotespace.org

立刻按 ctrl+D收藏本页

你会得到大惊喜!!

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

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☆☆☆☆☆

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...

评分☆☆☆☆☆

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！

评分☆☆☆☆☆

我感觉啊，这本书写的条理很清晰，可是太简明扼要了好像，我读不懂。可我碰到的问题上面有介绍，我又没找到其它地方，我只有读这个，可我读不懂。我郁闷。