k近邻算法实现

本书是经典畅销图书《Python 核心编程（第二版）》的全新升级版本，总共分为 3 部分。 第 1 部分讲解了 Python 的一些通用应用，包括正则表达式、网络编程、Internet 客户端编程、多线程编程、GUI 编程、数据库编程、Microsoft Office 编程、扩展 Python 等内容。 第 2 部分 讲解了与 Web 开发相关的主题，包括 Web 客户端和服务器、CGI 和 WSGI 相关的 Web 编程、Diango Web 框架、云计算、高级 Web 服务。第 3 部分则为一个补充/实验章节，包括文本处理以及一些其他内容。 本书适合具有一定经验的 Python 开发人员阅读(This book is a new upgraded version of the classic best-selling book Python Core Programming (2nd Edition). It is divided into three parts. Part 1 explains some general applications of Python, including regular expressions, network programming, Internet client programming, multi-threading programming, GUI programming, database programming, Microsoft Office programming, extension of Python and so on. Part 2 Topics related to Web development are explained, including Web client and server, CGI and WSGI related Web programming, Diango Web framework, cloud computing, advanced Web services. Part 3 is a supplementary/experimental chapter, including text processing and some other contents. This book is suitable for Python developers with some experience.)

采用卡尔曼滤波的方法对两只股票走势相近的股票进行预测，进行低买高卖的操作，从中获利。(Kalman filter method is used to predict two stocks with similar trend, and the operation of buying low and selling high is carried out to profit from it.)

说明：  利用深度神经网络去实现对物体的检测和分类(Detection and Classification of Objects Using Depth Neural Network)

统计学习是计算机及其应用领域的一门重要的学科本书全面系统地介绍了统计学习的主要方法，特别是监督学习方法，包括感知机、K近邻法、朴素贝叶斯法、决策树、逻辑斯谛回归、与最大熵模型、支持向量机、提升方法、EM算法、隐马尔可夫模型和条件随机场等。(Statistical learning is an important subject in the field of computer and application of this book comprehensively systematically introduces the main methods of statistical learning, especially the supervision method of study, including the perception, K neighbor method, naive bayesian method, decision tree, logistic regression, and the maximum entropy model, support vector machine (SVM), promotion methods, the EM algorithm, the hidden markov model and conditional random field, etc.)

机器深度学习的入门好书，能够帮助学习python机器学习快速入门！(A good introduction to machine-based in-depth learning!)

这是一个量子粒子群优化算法

Slycot Library for linear system utitlities

xml解析方法封装，便于直接解析xml中的value值(python for xml file parser)

说明：  考虫网的爬虫，可以通过编写url的方式自动将数据爬取到本地(The crawler of the web and automatically writes to excel)

2004年提出的Scale Invariant Feature Transform (SIFT) 是改进的基于尺度不变的特征检测器。 SIFT特征包括兴趣点检测器和描述子，它对于尺度，旋转和亮度都具有不变性。 可以进行sift特征的提取及进行两个图片的匹配