[{"title":"( 38 个子文件 169.35MB ) 邹博机器学习ppt+code(全)","children":[{"title":"ppt_code","children":[{"title":"13.SVM.pdf <span style='color:#111;'> 2.33MB </span>","children":null,"spread":false},{"title":"11.提升.pdf <span style='color:#111;'> 1.68MB </span>","children":null,"spread":false},{"title":"18.EM代码.zip <span style='color:#111;'> 13.86KB </span>","children":null,"spread":false},{"title":"12.XGBoost代码.zip <span style='color:#111;'> 137.58KB </span>","children":null,"spread":false},{"title":"10.RandomForest代码.zip <span style='color:#111;'> 32.44MB </span>","children":null,"spread":false},{"title":"22.主题模型实践.pdf <span style='color:#111;'> 2.39MB </span>","children":null,"spread":false},{"title":"8.回归实践.pdf <span style='color:#111;'> 2.78MB </span>","children":null,"spread":false},{"title":"15.聚类.pdf <span style='color:#111;'> 6.59MB </span>","children":null,"spread":false},{"title":"14.SVM实践.pdf <span style='color:#111;'> 1.85MB </span>","children":null,"spread":false},{"title":"1.机器学习与数学分析.pdf <span style='color:#111;'> 5.92MB </span>","children":null,"spread":false},{"title":"6.7.WordCloud.zip <span style='color:#111;'> 1.36KB </span>","children":null,"spread":false},{"title":"17.EM算法.pdf <span style='color:#111;'> 1.76MB </span>","children":null,"spread":false},{"title":"16.聚类实践.pdf <span style='color:#111;'> 1.98MB </span>","children":null,"spread":false},{"title":"18.EM算法实践.pdf <span style='color:#111;'> 1.62MB </span>","children":null,"spread":false},{"title":"5.Python库.pdf <span style='color:#111;'> 4.20MB </span>","children":null,"spread":false},{"title":"23.HMM.pdf <span style='color:#111;'> 1.71MB </span>","children":null,"spread":false},{"title":"19.贝叶斯网络.pdf <span style='color:#111;'> 3.34MB </span>","children":null,"spread":false},{"title":"4.Python基础.pdf <span style='color:#111;'> 1.46MB </span>","children":null,"spread":false},{"title":"14.SVM代码.zip <span style='color:#111;'> 13.85MB </span>","children":null,"spread":false},{"title":"4.Python代码.zip <span style='color:#111;'> 15.36KB </span>","children":null,"spread":false},{"title":"2.概率论与贝叶斯先验.pdf <span style='color:#111;'> 3.95MB </span>","children":null,"spread":false},{"title":"9.决策树和随机森林.pdf <span style='color:#111;'> 2.69MB </span>","children":null,"spread":false},{"title":"22.LDA_代码.zip <span style='color:#111;'> 5.32MB </span>","children":null,"spread":false},{"title":"8.Regression代码.zip <span style='color:#111;'> 37.89KB </span>","children":null,"spread":false},{"title":"6.数据清洗和特征选择.pdf <span style='color:#111;'> 2.12MB </span>","children":null,"spread":false},{"title":"12.XGBoost实践.pdf <span style='color:#111;'> 1.38MB </span>","children":null,"spread":false},{"title":"24.HMM_代码.zip <span style='color:#111;'> 32.30MB </span>","children":null,"spread":false},{"title":"7.回归.pdf <span style='color:#111;'> 4.20MB </span>","children":null,"spread":false},{"title":"6.Data代码.zip <span style='color:#111;'> 13.75MB </span>","children":null,"spread":false},{"title":"5.Package代码.zip <span style='color:#111;'> 746.20KB </span>","children":null,"spread":false},{"title":"10.决策树和随机森林实践.pdf <span style='color:#111;'> 1.48MB </span>","children":null,"spread":false},{"title":"24.HMM实践.pdf <span style='color:#111;'> 2.72MB </span>","children":null,"spread":false},{"title":"20.BayesianNetwork代码.zip <span style='color:#111;'> 2.59MB </span>","children":null,"spread":false},{"title":"20.贝叶斯网络实践.pdf <span style='color:#111;'> 1.41MB </span>","children":null,"spread":false},{"title":"21.主题模型.pdf <span style='color:#111;'> 2.69MB </span>","children":null,"spread":false},{"title":"3.矩阵和线性代数.pdf <span style='color:#111;'> 2.25MB </span>","children":null,"spread":false},{"title":"16.Clustering代码.zip <span style='color:#111;'> 3.15MB </span>","children":null,"spread":false},{"title":"xgboost-master-(windows上的编译包).zip <span style='color:#111;'> 1.13MB </span>","children":null,"spread":false}],"spread":false}],"spread":true}]