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Name		Name	Last commit message	Last commit date
Latest commit   History 19 Commits 19 Commits
Lesson-24-bank-additional-names.txt		Lesson-24-bank-additional-names.txt
Lesson1-Python Installation安装.ipynb		Lesson1-Python Installation安装.ipynb
Lesson1-Python序言及安装.docx		Lesson1-Python序言及安装.docx
Lesson10-Classes, Variables, Methods and Objects.ipynb		Lesson10-Classes, Variables, Methods and Objects.ipynb
Lesson11-Univariate,Bivariate and MultiVariate单变量多变量分析及柱状图.ipynb		Lesson11-Univariate,Bivariate and MultiVariate单变量多变量分析及柱状图.ipynb
Lesson12-Linear Regression Math.xlsx		Lesson12-Linear Regression Math.xlsx
Lesson13-50_Startups.csv		Lesson13-50_Startups.csv
Lesson13-Python进阶ML-MultipleLinear Regression多元线性回归.ipynb		Lesson13-Python进阶ML-MultipleLinear Regression多元线性回归.ipynb
Lesson14-Python进阶ML-Polynomial (Linear) Regression多项式(线性)回归.ipynb		Lesson14-Python进阶ML-Polynomial (Linear) Regression多项式(线性)回归.ipynb
Lesson14-age-height.xlsx		Lesson14-age-height.xlsx
Lesson15 Keynote.docx		Lesson15 Keynote.docx
Lesson15-Python进阶ML-MultiCollinearity In Linear Regression多重共线性及VIF.ipynb		Lesson15-Python进阶ML-MultiCollinearity In Linear Regression多重共线性及VIF.ipynb
Lesson15-Salary_Data.csv		Lesson15-Salary_Data.csv
Lesson16-实战Ridge & Lasso Regression解决线性回归的Overfitting过度拟合.ipynb		Lesson16-实战Ridge & Lasso Regression解决线性回归的Overfitting过度拟合.ipynb
Lesson17-diabetes.csv		Lesson17-diabetes.csv
Lesson17-应用Logistic Regression逻辑回归建模.ipynb		Lesson17-应用Logistic Regression逻辑回归建模.ipynb
Lesson18-如何对Data Set数据集进行清洗，转换，汇总及建模之完整步骤.ipynb		Lesson18-如何对Data Set数据集进行清洗，转换，汇总及建模之完整步骤.ipynb
Lesson19-使用Decision Trees建模with Gini and Entropy.ipynb		Lesson19-使用Decision Trees建模with Gini and Entropy.ipynb
Lesson2-Python Data Structures数据结构.ipynb		Lesson2-Python Data Structures数据结构.ipynb
Lesson20-petrol_consumption.csv		Lesson20-petrol_consumption.csv
Lesson20-使用Random Forests Classifiers&Regressor两种方式建模.ipynb		Lesson20-使用Random Forests Classifiers&Regressor两种方式建模.ipynb
Lesson21- 使用Adaboost建模及工作环境下的数据分析整理.ipynb		Lesson21- 使用Adaboost建模及工作环境下的数据分析整理.ipynb
Lesson21-adaboost.jpg		Lesson21-adaboost.jpg
Lesson21-titanic_test.csv		Lesson21-titanic_test.csv
Lesson21-titanic_train.csv		Lesson21-titanic_train.csv
Lesson22-Bagging vs Boosting&使用Xgboost和Gradient Boosting建模.ipynb		Lesson22-Bagging vs Boosting&使用Xgboost和Gradient Boosting建模.ipynb
Lesson22-adaboostvsGB.jpg		Lesson22-adaboostvsGB.jpg
Lesson22-bagging vs boosting.png		Lesson22-bagging vs boosting.png
Lesson22-compare.png		Lesson22-compare.png
Lesson22-compare1.png		Lesson22-compare1.png
Lesson22-xgb.png		Lesson22-xgb.png
Lesson23-Distance.png		Lesson23-Distance.png
Lesson23-K Nearest Neighbour(KNN)建模.ipynb		Lesson23-K Nearest Neighbour(KNN)建模.ipynb
Lesson23-KNN.png		Lesson23-KNN.png
Lesson23-minkowski.png		Lesson23-minkowski.png
Lesson24-SVM.png		Lesson24-SVM.png
Lesson24-SVM1.png		Lesson24-SVM1.png
Lesson24-Support Vector Machine建模.ipynb		Lesson24-Support Vector Machine建模.ipynb
Lesson24-bank-additional-full.csv		Lesson24-bank-additional-full.csv
Lesson25-Bayes贝叶斯识别Spam Email垃圾邮件.ipynb		Lesson25-Bayes贝叶斯识别Spam Email垃圾邮件.ipynb
Lesson25-card1.png		Lesson25-card1.png
Lesson25-card2.png		Lesson25-card2.png
Lesson25-spam_ham_dataset.csv		Lesson25-spam_ham_dataset.csv
Lesson26-Voting.png		Lesson26-Voting.png
Lesson26-Votingclassifier及11种算法全自动建模预测输出结果之完整源代码.ipynb		Lesson26-Votingclassifier及11种算法全自动建模预测输出结果之完整源代码.ipynb
Lesson26-voting1.png		Lesson26-voting1.png
Lesson27-Elbow method.png		Lesson27-Elbow method.png
Lesson27-Snow-cholera-map.jpg		Lesson27-Snow-cholera-map.jpg
Lesson27-Snow-cholera-map1.jpg		Lesson27-Snow-cholera-map1.jpg
Lesson27-cluster.png		Lesson27-cluster.png
Lesson27-income.xlsx		Lesson27-income.xlsx
Lesson27-k-means-steps.png		Lesson27-k-means-steps.png
Lesson27-无监督学习K Means Clustering.ipynb		Lesson27-无监督学习K Means Clustering.ipynb
Lesson28-Clustering_h1.png		Lesson28-Clustering_h1.png
Lesson28-Dendrogram.png		Lesson28-Dendrogram.png
Lesson28-Hierarchical Clustering哪些存量客户是新产品的目标用户.ipynb		Lesson28-Hierarchical Clustering哪些存量客户是新产品的目标用户.ipynb
Lesson28-customers data.csv		Lesson28-customers data.csv
Lesson28-scaling.png		Lesson28-scaling.png
Lesson29-Clustering1.png		Lesson29-Clustering1.png
Lesson29-DBSCAN-1.png		Lesson29-DBSCAN-1.png
Lesson29-DBSCAN-2.png		Lesson29-DBSCAN-2.png
Lesson29-DBSCAN.png		Lesson29-DBSCAN.png
Lesson29-DBSCAN聚类与K-means及Hierarchical Clustering区别.ipynb		Lesson29-DBSCAN聚类与K-means及Hierarchical Clustering区别.ipynb
Lesson29-Demo.gif		Lesson29-Demo.gif
Lesson29-Kmeans.png		Lesson29-Kmeans.png
Lesson3-Numpy, Seaborn库.ipynb		Lesson3-Numpy, Seaborn库.ipynb
Lesson30-B02512.png		Lesson30-B02512.png
Lesson30-B02617.png		Lesson30-B02617.png
Lesson30-uber-raw-data-aug14.rar		Lesson30-uber-raw-data-aug14.rar
Lesson30-纽约Uber数据分析图形化和K-means计算热点.ipynb		Lesson30-纽约Uber数据分析图形化和K-means计算热点.ipynb
Lesson31-KMeans clustering如何验证K点最佳 - silhouette analysis.ipynb		Lesson31-KMeans clustering如何验证K点最佳 - silhouette analysis.ipynb
Lesson31-Principal Component Analysis second principal.gif		Lesson31-Principal Component Analysis second principal.gif
Lesson31-PrincipalComponentAnalysis.jpg		Lesson31-PrincipalComponentAnalysis.jpg
Lesson31-iris_with_labels.jpg		Lesson31-iris_with_labels.jpg
Lesson32-无监督学习Principal Component Analysis(PCA)精简高维数据.ipynb		Lesson32-无监督学习Principal Component Analysis(PCA)精简高维数据.ipynb
Lesson33-12种聚类(无监督学习)算法说明和区分比较(一).ipynb		Lesson33-12种聚类(无监督学习)算法说明和区分比较(一).ipynb
Lesson33-Illustration-of-how-affinity-propagation-works.png		Lesson33-Illustration-of-how-affinity-propagation-works.png
Lesson33-Meanshift.gif		Lesson33-Meanshift.gif
Lesson33-cluster.png		Lesson33-cluster.png
Lesson33-clusterable_data.npy		Lesson33-clusterable_data.npy
Lesson33-example_contour_bw_2.png		Lesson33-example_contour_bw_2.png
Lesson33-example_kde_2.png		Lesson33-example_kde_2.png
Lesson33-mean-shift-finding-densest-regions.png		Lesson33-mean-shift-finding-densest-regions.png
Lesson33-preference_median.gif		Lesson33-preference_median.gif
Lesson34-12种聚类(无监督学习)算法说明和区分比较(二).ipynb		Lesson34-12种聚类(无监督学习)算法说明和区分比较(二).ipynb
Lesson34-3-Figure3-1.png		Lesson34-3-Figure3-1.png
Lesson34-3-Figure3-2.png		Lesson34-3-Figure3-2.png
Lesson34-Figure8-1.png		Lesson34-Figure8-1.png
Lesson34-example-of-the-birch-algorithm-l.jpg		Lesson34-example-of-the-birch-algorithm-l.jpg
Lesson34-spectral-clustering.jpg		Lesson34-spectral-clustering.jpg
Lesson34-ward.png		Lesson34-ward.png
Lesson35-12种聚类(无监督学习)算法说明和区分比较(三).ipynb		Lesson35-12种聚类(无监督学习)算法说明和区分比较(三).ipynb
Lesson35-GMM.png		Lesson35-GMM.png
Lesson35-GMM1.png		Lesson35-GMM1.png
Lesson35-GMM3.png		Lesson35-GMM3.png
Lesson35-HDBSCAN.pdf		Lesson35-HDBSCAN.pdf
Lesson35-HDBSCAN.png		Lesson35-HDBSCAN.png
Lesson35-HDBSCAN1.png		Lesson35-HDBSCAN1.png
Lesson35-HDBSCAN2.png		Lesson35-HDBSCAN2.png
Lesson35-HDBSCAN3.png		Lesson35-HDBSCAN3.png
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