"""
bishop – Pattern Recognition and Machine Learning (Christopher Bishop)
======================================================================
Thin wrappers over existing libraries with unified interfaces, organised
by PRML chapter.  Novel gaps (e.g. RVM, particle filter) are implemented
from scratch only where no production library covers them.

Modules
-------
linear_models   – Ch 3-4: sklearn BayesianRidge, LogisticRegression, + RVM
neural_networks – Ch 5: PyTorch MLP / training helpers
kernel_methods  – Ch 6-7: sklearn SVM, GP; custom RVM kernel variant
graphical_models– Ch 8: pgmpy Bayesian nets + hmmlearn HMMs
mixture_models  – Ch 9: sklearn GMM / EM
sampling        – Ch 11: pymc MCMC wrappers + custom Metropolis-Hastings
dimensionality  – Ch 12: sklearn PCA, FastICA, LDA, KernelPCA
sequential      – Ch 13: filterpy Kalman filter + custom particle filter
"""
