Graphical Models for Machine Learning and Digital Communication pdf epub mobi txt 電子書 下載2025
- 機器學習
- 概率模型
- 圖模型
- 計算機科學
- 概率論
- 數學
- 加拿大
- PGM
- Graphical Models
- Machine Learning
- Digital Communication
- Probabilistic Models
- Bayesian Networks
- Factor Graphs
- Inference Algorithms
- Information Theory
- Signal Processing
- Pattern Recognition
具體描述
A variety of problems in machine learning and digital communication deal with complex but structured natural or artificial systems. In this book, Brendan Frey uses graphical models as an overarching framework to describe and solve problems of pattern classification, unsupervised learning, data compression, and channel coding. Using probabilistic structures such as Bayesian belief networks and Markov random fields, he is able to describe the relationships between random variables in these systems and to apply graph-based inference techniques to develop new algorithms. Among the algorithms described are the wake-sleep algorithm for unsupervised learning, the iterative turbodecoding algorithm (currently the best error-correcting decoding algorithm), the bits-back coding method, the Markov chain Monte Carlo technique, and variational inference.
著者簡介
Brendan J. Frey Professor
Electrical and Computer Engineering
University of Toronto
圖書目錄
讀後感
評分
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用戶評價
呃，覺得就是瞭解個框架吧。講的都不詳細。尤其關於digital的舉例非常不適應，看起來比較愣。
评分呃，覺得就是瞭解個框架吧。講的都不詳細。尤其關於digital的舉例非常不適應，看起來比較愣。
评分呃，覺得就是瞭解個框架吧。講的都不詳細。尤其關於digital的舉例非常不適應，看起來比較愣。
评分呃，覺得就是瞭解個框架吧。講的都不詳細。尤其關於digital的舉例非常不適應，看起來比較愣。
评分呃，覺得就是瞭解個框架吧。講的都不詳細。尤其關於digital的舉例非常不適應，看起來比較愣。
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