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说明：  利用python进行数据分析，英文书籍，从pandas库的数据分析工具开始利用高性能工具对数据进行加载、清理、转换、合并以及重塑；利用matpIotlib创建散点图以及静态或交互式的可视化结果；利用pandas的groupby功能对数据集进行切片、切块和汇总操作；处理各种各样的时间序列数据。(Starting from the data analysis tools of pandas database, high performance tools are used to load, clean, transform, merge and remodel data; scatter plots and static or interactive visualization results are created by matpIotlib; data sets are sliced, sliced and aggregated by pandas group by function; and various operations are processed. Time series data.)

一个xgboost实现的回归模型预测，数据集来源于kaggle的taxi竞赛(Regression model prediction based on a xgboost implementation)

1基于MapReduce的K-Means聚类算法， 2基于MapReduce的分类算法 3MapReduce的频繁项集挖掘算法(1 K-Means clustering algorithm based on MapReduce, 2 classification algorithm based on MapReduce 3 Mining Algorithm for frequent itemsets based on MapReduce)

Numerical Recipes Software 提供的算法子程序集,一共有上千种算法,部分算法可以在书店买到书()

徐士良《C常用算法程序集》第2版 第2部分()

PCA源程序，主元分析源程序，可以用于变量的特征提取(PCA source code, principal component analysis source, can be used for variable feature extraction)

说明：  用matlab 实现了kmeans算法还附有评价指标计算(Matlab to achieve kmeans algorithm also attached to the evaluation index calculation)

SMOTE插值算法，补全数据的不平衡性。(SMOTE interpolation algorithm to complete the imbalance of data.)

通过贝叶斯信息准则确定高斯混合聚类方法的聚类簇数(Determining the Cluster Number of GMM Clusters by BIC)

使用python实现谱减法对语音的降噪功能，代码包括语音的读取、降噪、输出保存(Spectral subtraction speech noise reduction python code)