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Pattern Recognition and Machine Learning (Solutions to the Exercises: Tutors’ Edition)

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This is the solutions manual (Tutors’ Edition) for the book Pattern Recognition and Machine Learning (PRML; published by Springer in 2006). This release was created September 8, 2009. Any future releases (e.g. with corrections to errors) will be announced on the PRML web-site (see below) and published via Springer.

Author(s): Christopher Bishop
Series: Information Science and Statistics
Publisher: Springer
Year: 2007

Language: English
Pages: 254
Tags: Intelligence Semantics AI Machine Learning Computer Science Computers Technology Vision Pattern Recognition Graphics Design Adobe CAD Modelling Desktop Publishing Electronic Documents Rendering Ray Tracing User Experience Usability Multimedia DirectX Flash GIS OpenGL Solid Works Programming Probability Statistics Applied Mathematics Math Artificial New Used Rental Textbooks Specialty Boutique Visualization

Chapter1:Introduction
Chapter2:ProbabilityDistributions
Chapter3:LinearModelsforRegression
Chapter4:LinearModelsforClassification
Chapter5:NeuralNetworks
Chapter6:KernelMethods
Chapter7:SparseKernelMachines
Chapter8:GraphicalModels
Chapter9:MixtureModelsandEM
Chapter10:ApproximateInference
Chapter11:SamplingMethods
Chapter12:ContinuousLatentVariables
Chapter13:SequentialData
Chapter14:CombiningModels