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Python数据科学手册/#/Python数据科学手册 [ by Jake VanderPlas; 陶俊杰 陈小莉 is a nonfiction available to read on EtoBox.

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Introduction. Example : Polynomial Curve Fitting ; Probability Theory ; Model Selection ; The Curse Of Dimensionality Decision Theory ; Information Theory -- Probability Distributions. Binary Vehicles ; Multinomial Variables ; The Gaussian Distribution ; The Exponential Family ; Nonparametric Methods -- Linear Models For Regression. Linear Basis Function Models ; The Bias-variance Decomposition ; Bayesian Linear Regression ; Bayesian Model Comparison ; The Evidence Approximation ; Limitations Of Fixed Basis Functions -- Linear Models For Classification. Discriminant Functions ; Probabilistic Generative Models ; Probabilistic Discrimitive Models ; The Laplace Approximation ; Bayesian Logistic Regression -- Neural Networks. Feed-forward Network Functions ; Network Training ; Error Backpropagation ; The Hessian Matrix ; Regularization In Neural Networks ; Mixture Density Networks ; Bayesian Neural Networks. Kernel Methods. Dual Representations ; Constructing Kernals ; Radial Basis Function Networks ; Gaussian Processes -- Sparse Kernel Machines. Maximum Margin Classifiers ; Relevance Vector Machines -- Graphical Models. Bayesian Networks ; Conditional Independence ; Markov Random Fiel

Who reads Python数据科学手册/#/Python数据科学手册 [?

Author

Jake VanderPlas; 陶俊杰 陈小莉

Publisher

北京：人民邮电出版社

Published

2018

Language

EN

ISBN

9787115475893

Category

nonfiction

Subjects

Science, Mathematics, Stem

Rating

4.25 / 5 (969 ratings)

Updated

2026-03-13