史上最全的菜菜的sklearn学习[教程很详细].rar

[{"title":"（ 79 个子文件 151.84MB ） 史上最全的菜菜的sklearn学习[教程很详细].rar","children":[{"title":"菜菜sklearn","children":[{"title":"参考书1.jpg <span style='color:#111;'> 100.77KB </span>","children":null,"spread":false},{"title":"参考书3.jpg <span style='color:#111;'> 89.76KB </span>","children":null,"spread":false},{"title":"09回归大家族：线性回归，岭回归，Lasso与多项式回归","children":[{"title":"线性回归大家族 full version.pdf <span style='color:#111;'> 4.98MB </span>","children":null,"spread":false},{"title":"线性回归 - 代码.ipynb <span style='color:#111;'> 473.35KB </span>","children":null,"spread":false},{"title":"线性回归 课件 + 代码.zip <span style='color:#111;'> 4.92MB </span>","children":null,"spread":false}],"spread":true},{"title":"08支持向量机下","children":[{"title":".ipynb_checkpoints","children":[{"title":"SVM 2 - 理论部分源码-checkpoint.ipynb <span style='color:#111;'> 661.53KB </span>","children":null,"spread":false}],"spread":true},{"title":"cityll.csv <span style='color:#111;'> 4.11KB </span>","children":null,"spread":false},{"title":"SVM数据.zip <span style='color:#111;'> 4.24MB </span>","children":null,"spread":false},{"title":"SVM 2 - 案例部分源码.ipynb <span style='color:#111;'> 373.03KB </span>","children":null,"spread":false},{"title":"weather.csv <span style='color:#111;'> 15.15MB </span>","children":null,"spread":false},{"title":"SVM (下) full version.pdf <span style='color:#111;'> 3.33MB </span>","children":null,"spread":false},{"title":"Cityclimate.csv <span style='color:#111;'> 3.69KB </span>","children":null,"spread":false},{"title":"SVM 2 - 理论部分源码.ipynb <span style='color:#111;'> 661.53KB </span>","children":null,"spread":false},{"title":"weatherAUS5000.csv <span style='color:#111;'> 538.55KB </span>","children":null,"spread":false},{"title":"SVM (下) - 源码.zip <span style='color:#111;'> 221.88KB </span>","children":null,"spread":false},{"title":"samplecity.csv <span style='color:#111;'> 2.03KB </span>","children":null,"spread":false},{"title":"SVM (下) full version.xml <span style='color:#111;'> 31.34KB </span>","children":null,"spread":false}],"spread":false},{"title":"06聚类算法Kmeans","children":[{"title":"聚类算法与Kmeans代码.zip <span style='color:#111;'> 2.52MB </span>","children":null,"spread":false},{"title":".ipynb_checkpoints","children":[{"title":"聚类算法与Kmeans-checkpoint.ipynb <span style='color:#111;'> 3.39MB </span>","children":null,"spread":false}],"spread":true},{"title":"聚类算法与Kmeans.ipynb <span style='color:#111;'> 3.39MB </span>","children":null,"spread":false},{"title":"聚类算法KMeans EDU version.pdf <span style='color:#111;'> 2.19MB </span>","children":null,"spread":false}],"spread":true},{"title":"05逻辑回归与评分卡","children":[{"title":".ipynb_checkpoints","children":[{"title":"评分卡模型-checkpoint.ipynb <span style='color:#111;'> 265.60KB </span>","children":null,"spread":false},{"title":"逻辑回归-checkpoint.ipynb <span style='color:#111;'> 233.88KB </span>","children":null,"spread":false}],"spread":true},{"title":"vali_data.csv <span style='color:#111;'> 8.77MB </span>","children":null,"spread":false},{"title":"逻辑回归 full version.pdf <span style='color:#111;'> 3.03MB </span>","children":null,"spread":false},{"title":"rankingcard.csv <span style='color:#111;'> 7.21MB </span>","children":null,"spread":false},{"title":"逻辑回归 full version.xml <span style='color:#111;'> 31.19KB </span>","children":null,"spread":false},{"title":"评分卡模型.ipynb <span style='color:#111;'> 265.60KB </span>","children":null,"spread":false},{"title":"ScoreData.csv <span style='color:#111;'> 1.83KB </span>","children":null,"spread":false},{"title":"逻辑回归课件 + 数据.zip <span style='color:#111;'> 5.84MB </span>","children":null,"spread":false},{"title":"model_data.csv <span style='color:#111;'> 20.54MB </span>","children":null,"spread":false},{"title":"逻辑回归.ipynb <span style='color:#111;'> 55.08KB </span>","children":null,"spread":false}],"spread":true},{"title":"011XGBoost","children":[{"title":".ipynb_checkpoints","children":[{"title":"Untitled-checkpoint.ipynb <span style='color:#111;'> 72B </span>","children":null,"spread":false},{"title":"xgboost code-checkpoint.ipynb <span style='color:#111;'> 611.49KB </span>","children":null,"spread":false}],"spread":true},{"title":"XGBoost full version.pdf <span style='color:#111;'> 5.31MB </span>","children":null,"spread":false},{"title":"xgboost code.ipynb <span style='color:#111;'> 611.80KB </span>","children":null,"spread":false},{"title":"xgboost 代码 + 课件.zip <span style='color:#111;'> 5.36MB </span>","children":null,"spread":false}],"spread":true},{"title":"07支持向量机上","children":[{"title":".ipynb_checkpoints","children":[{"title":"SVM1-checkpoint.ipynb <span style='color:#111;'> 1.23MB </span>","children":null,"spread":false}],"spread":true},{"title":"Record.ipynb <span style='color:#111;'> 30.92KB </span>","children":null,"spread":false},{"title":"SVM (上) full version.pdf <span style='color:#111;'> 7.72MB </span>","children":null,"spread":false},{"title":"SVM1.ipynb <span style='color:#111;'> 1.23MB </span>","children":null,"spread":false},{"title":"SVM (上) full version.xml <span style='color:#111;'> 21.32KB </span>","children":null,"spread":false}],"spread":true},{"title":"010朴素贝叶斯","children":[{"title":"010朴素贝叶斯.rar <span style='color:#111;'> 4.13MB </span>","children":null,"spread":false},{"title":"Naive Bayes源码.ipynb <span style='color:#111;'> 2.99MB </span>","children":null,"spread":false},{"title":"朴素贝叶斯 full version.pdf <span style='color:#111;'> 3.40MB </span>","children":null,"spread":false}],"spread":true},{"title":"03数据预处理和特征工程","children":[{"title":".ipynb_checkpoints","children":[{"title":"record-checkpoint.ipynb <span style='color:#111;'> 132.92KB </span>","children":null,"spread":false}],"spread":true},{"title":"digit recognizor.csv <span style='color:#111;'> 73.22MB </span>","children":null,"spread":false},{"title":"record.ipynb <span style='color:#111;'> 132.92KB </span>","children":null,"spread":false},{"title":"Narrativedata.csv <span style='color:#111;'> 17.96KB </span>","children":null,"spread":false},{"title":"数据预处理和特征工程 - 数据.zip <span style='color:#111;'> 8.91MB </span>","children":null,"spread":false},{"title":"数据预处理与特征工程 full version.xml <span style='color:#111;'> 19.11KB </span>","children":null,"spread":false},{"title":"数据预处理与特征工程 full version.pdf <span style='color:#111;'> 2.58MB </span>","children":null,"spread":false}],"spread":true},{"title":"开始机器学习之前：配置开发环境.pdf <span style='color:#111;'> 1.64MB </span>","children":null,"spread":false},{"title":"02随机森林","children":[{"title":".ipynb_checkpoints","children":null,"spread":false},{"title":"Record.ipynb <span style='color:#111;'> 242.04KB </span>","children":null,"spread":false},{"title":"train.csv <span style='color:#111;'> 73.22MB </span>","children":null,"spread":false},{"title":"digit recognizor.zip <span style='color:#111;'> 14.88MB </span>","children":null,"spread":false},{"title":"sample_submission.csv <span style='color:#111;'> 235.26KB </span>","children":null,"spread":false},{"title":"test.csv <span style='color:#111;'> 48.75MB </span>","children":null,"spread":false},{"title":"随机森林 full version.pdf <span style='color:#111;'> 2.46MB </span>","children":null,"spread":false}],"spread":true},{"title":"04主成分分析PCA与奇异值分解SVD","children":[{"title":".ipynb_checkpoints","children":[{"title":"Record-checkpoint.ipynb <span style='color:#111;'> 350.34KB </span>","children":null,"spread":false},{"title":"record2-checkpoint.ipynb <span style='color:#111;'> 72B </span>","children":null,"spread":false}],"spread":true},{"title":"digit recognizor.csv <span style='color:#111;'> 73.22MB </span>","children":null,"spread":false},{"title":"Record.ipynb <span style='color:#111;'> 350.34KB </span>","children":null,"spread":false},{"title":"record2.ipynb <span style='color:#111;'> 92.53KB </span>","children":null,"spread":false},{"title":"降维算法 full version.xml <span style='color:#111;'> 35.02KB </span>","children":null,"spread":false},{"title":"降维算法 full version.pdf <span style='color:#111;'> 2.71MB </span>","children":null,"spread":false}],"spread":true},{"title":"参考书2.jpg <span style='color:#111;'> 93.00KB </span>","children":null,"spread":false},{"title":"01 决策树课件数据源码","children":[{"title":"Tree.dot <span style='color:#111;'> 1.56KB </span>","children":null,"spread":false},{"title":".ipynb_checkpoints","children":[{"title":"决策树 原理部分源码-checkpoint.ipynb <span style='color:#111;'> 178.49KB </span>","children":null,"spread":false},{"title":"决策树 案例部分源码-checkpoint.ipynb <span style='color:#111;'> 35.42KB </span>","children":null,"spread":false}],"spread":false},{"title":"data.csv <span style='color:#111;'> 59.76KB </span>","children":null,"spread":false},{"title":"决策树 原理部分源码.ipynb <span style='color:#111;'> 178.49KB </span>","children":null,"spread":false},{"title":"决策树原理更新.pdf <span style='color:#111;'> 3.60MB </span>","children":null,"spread":false},{"title":"Taitanic data.zip <span style='color:#111;'> 32.50KB </span>","children":null,"spread":false},{"title":"Tree <span style='color:#111;'> 2.03KB </span>","children":null,"spread":false},{"title":"test.csv <span style='color:#111;'> 27.96KB </span>","children":null,"spread":false},{"title":"决策树 案例部分源码.ipynb <span style='color:#111;'> 35.42KB </span>","children":null,"spread":false},{"title":"Tree.pdf <span style='color:#111;'> 28.30KB </span>","children":null,"spread":false},{"title":"决策树 full version.pdf <span style='color:#111;'> 3.31MB </span>","children":null,"spread":false}],"spread":false}],"spread":false}],"spread":true}]