介绍模式识别的基本概念，详述了贝叶斯，参数估计，线性分类器，神经网络，随机方法，无监督学习与聚类等-Introduce the basic concepts of pattern recognition, Bayesian detailed, parameter estimation, linear classifiers, neural networks, stochastic methods, unsupervised learning and clustering, etc.

关于LDA代码的学习，使用吉布斯抽样进行参数估计-Learning about the LDA code, using gibbs sampling for parameter estimation