Information Theory, Inference, and Learning Algorithms

Information Theory, Inference, and Learning Algorithms

Information Theory, Inference, and Learning Algorithms is available free online.

Description

This book is divided into six parts as Data Compression, Noisy-Channel Coding, Further Topics in Information Theory, Probabilities and Inference, Neural networks, Sparse Graph Codes.

Table of Contents

  • Introduction to Information Theory
  • Probability, Entropy, and Inference
  • More about Inference
  • The Source Coding Theorem
  • Symbol Codes
  • Stream Codes
  • Codes for Integers
  • Dependent Random Variables
  • Communication over a Noisy Channel
  • The Noisy-Channel Coding Theorem
  • Error-Correcting Codes and Real Channels
  • Hash Codes: Codes for Efficient Information Retrieval
  • Binary Codes
  • Very Good Linear Codes Exist
  • Further Exercises on Information Theory
  • Message Passing
  • Communication over Constrained Noiseless Channels
  • Crosswords and Codebreaking
  • Why have Sex? Information Acquisition and Evolution
  • An Example Inference Task: Clustering
  • Exact Inference by Complete Enumeration
  • Maximum Likelihood and Clustering
  • Useful Probability Distributions
  • Exact Marginalization
  • Exact Marginalization in Trellises
  • Exact Marginalization in Graphs
  • Laplace’s Method
  • Model Comparison and Occam’s Razor
  • Monte Carlo Methods
  • Efficient Monte Carlo Methods
  • Ising Models
  • Exact Monte Carlo Sampling
  • Variational Methods
  • Independent Component Analysis and Latent Variable Modelling
  • Random Inference Topics
  • Decision Theory
  • Bayesian Inference and Sampling Theory
  • Introduction to Neural Networks
  • The Single Neuron as a Classifier
  • Capacity of a Single Neuron
  • Learning as Inference
  • Hopfield Networks
  • Boltzmann Machines
  • Supervised Learning in Multilayer Networks
  • Gaussian Processes
  • Deconvolution
  • Low-Density Parity-Check Codes
  • Convolutional Codes and Turbo Codes
  • Repeat-Accumulate Codes
  • Digital Fountain Codes

Book Details

Author(s): David J.C. MacKay
Format(s): PDF
File size: 9.0 MB
Number of pages: 640
Link: Download.








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