GitHub - baiqz/LessonPythonCode: LessonPythonCode

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Name		Name	Last commit message	Last commit date
Latest commit History 98 Commits
Lesson109-yolo		Lesson109-yolo
Lesson40-Model-Deployment-Flask		Lesson40-Model-Deployment-Flask
Lesson41-Model-Deployment-Streamlit		Lesson41-Model-Deployment-Streamlit
Lesson72-使用flask建立图像识别小程序Demo		Lesson72-使用flask建立图像识别小程序Demo
Lesson82-Face-Mask-Detection		Lesson82-Face-Mask-Detection
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
Lesson100-1.png		Lesson100-1.png
Lesson100-2.png		Lesson100-2.png
Lesson100-Naive Bayes (Classifier)算法特征.ipynb		Lesson100-Naive Bayes (Classifier)算法特征.ipynb
Lesson101-1.png		Lesson101-1.png
Lesson101-2.png		Lesson101-2.png
Lesson101-4.png		Lesson101-4.png
Lesson101-SVM算法特征.ipynb		Lesson101-SVM算法特征.ipynb
Lesson102-2.png		Lesson102-2.png
Lesson102-3.png		Lesson102-3.png
Lesson102-One-Vs-Rest and One-Vs-One Multi-Class Classification.ipynb		Lesson102-One-Vs-Rest and One-Vs-One Multi-Class Classification.ipynb
Lesson103-1.png		Lesson103-1.png
Lesson103-LinearSVC or SVC of SVM.ipynb		Lesson103-LinearSVC or SVC of SVM.ipynb
Lesson104-3.png		Lesson104-3.png
Lesson104-SVM Kernels 及手工验证实现Polynomial Kernels.ipynb		Lesson104-SVM Kernels 及手工验证实现Polynomial Kernels.ipynb
Lesson105-1.png		Lesson105-1.png
Lesson105-Imbalanced Data对于SVM影响以及C的作用.ipynb		Lesson105-Imbalanced Data对于SVM影响以及C的作用.ipynb
Lesson106-Imbalanced Data对于算法的影响.ipynb		Lesson106-Imbalanced Data对于算法的影响.ipynb
Lesson107-ANN Activation, Kernel_initialize, Optimizer, Loss, Output总结.ipynb		Lesson107-ANN Activation, Kernel_initialize, Optimizer, Loss, Output总结.ipynb
Lesson107-SGDvGD.png		Lesson107-SGDvGD.png
Lesson108-应用Transfer Learning和Vgg 16识别厨房刀具.ipynb		Lesson108-应用Transfer Learning和Vgg 16识别厨房刀具.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
Lesson110-1.png		Lesson110-1.png
Lesson110-2.jpg		Lesson110-2.jpg
Lesson110-3.jpg		Lesson110-3.jpg
Lesson110-4.png		Lesson110-4.png
Lesson110-5.png		Lesson110-5.png
Lesson110-MSE,RMSE,MAE.ipynb		Lesson110-MSE,RMSE,MAE.ipynb
Lesson111-1.png		Lesson111-1.png
Lesson111-2.png		Lesson111-2.png
Lesson111-3.png		Lesson111-3.png
Lesson111-4.png		Lesson111-4.png
Lesson111-5.png		Lesson111-5.png
Lesson111-How many Samplings.ipynb		Lesson111-How many Samplings.ipynb
Lesson112-2.png		Lesson112-2.png
Lesson112-4.png		Lesson112-4.png
Lesson112-5.png		Lesson112-5.png
Lesson112-Normal_distribution_and_scales.gif		Lesson112-Normal_distribution_and_scales.gif
Lesson112-Z-Score & Standard Deviations.ipynb		Lesson112-Z-Score & Standard Deviations.ipynb
Lesson113-1.png		Lesson113-1.png
Lesson113-2.png		Lesson113-2.png
Lesson113-4.png		Lesson113-4.png
Lesson113-5.png		Lesson113-5.png
Lesson113-6.png		Lesson113-6.png
Lesson113-7.png		Lesson113-7.png
Lesson113-8.jpg		Lesson113-8.jpg
Lesson113-P-Value & Z-Score.ipynb		Lesson113-P-Value & Z-Score.ipynb
Lesson114-P-Value & Hypothese Test.ipynb		Lesson114-P-Value & Hypothese Test.ipynb
Lesson115-Hypothese Test & Correlation Tests & Stationary Tests.ipynb		Lesson115-Hypothese Test & Correlation Tests & Stationary Tests.ipynb
Lesson116-1.jpeg		Lesson116-1.jpeg
Lesson116-2.png		Lesson116-2.png
Lesson116-Parametric Statistical Hypothesis Tests & Nonparametric.ipynb		Lesson116-Parametric Statistical Hypothesis Tests & Nonparametric.ipynb
Lesson116-t-test-formula.jpg		Lesson116-t-test-formula.jpg
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