菜菜机器学习课件

[{"title":"（ 18 个子文件 64.01MB ） 菜菜机器学习课件","children":[{"title":"菜菜机器学习课件","children":[{"title":"06-聚类算法K-Means.pdf <span style='color:#111;'> 2.01MB </span>","children":null,"spread":false},{"title":"12-神经网络.pdf <span style='color:#111;'> 2.12MB </span>","children":null,"spread":false},{"title":"01-决策树在sklearn中的实现&调参.pdf <span style='color:#111;'> 1.79MB </span>","children":null,"spread":false},{"title":".DS_Store <span style='color:#111;'> 8.00KB </span>","children":null,"spread":false},{"title":"08-支持向量机(下)","children":[{"title":".DS_Store <span style='color:#111;'> 6.00KB </span>","children":null,"spread":false},{"title":"08-支持向量机SVM-案例直播课.pdf <span style='color:#111;'> 2.32MB </span>","children":null,"spread":false},{"title":"SVM live code.ipynb <span style='color:#111;'> 7.79KB </span>","children":null,"spread":false}],"spread":true},{"title":"09-线性回归和回归类模型的评估指标.pdf <span style='color:#111;'> 2.05MB </span>","children":null,"spread":false},{"title":"10-朴素贝叶斯.pdf <span style='color:#111;'> 2.19MB </span>","children":null,"spread":false},{"title":"03-sklearn中的数据预处理","children":[{"title":"Narrativedata.csv <span style='color:#111;'> 17.96KB </span>","children":null,"spread":false},{"title":".DS_Store <span style='color:#111;'> 6.00KB </span>","children":null,"spread":false},{"title":"digit recognizor.csv <span style='color:#111;'> 73.22MB </span>","children":null,"spread":false},{"title":"03-sklearn中的数据预处理和特征工程.pdf <span style='color:#111;'> 1.50MB </span>","children":null,"spread":false}],"spread":true},{"title":"02-随机森林在sklearn中的实现&调参.pdf <span style='color:#111;'> 1.87MB </span>","children":null,"spread":false},{"title":"07-支持向量机(上).pdf <span style='color:#111;'> 3.29MB </span>","children":null,"spread":false},{"title":"04sklearn中的降维算法PCA和SVD.pdf <span style='color:#111;'> 32.91MB </span>","children":null,"spread":false},{"title":"05-逻辑回归.pdf <span style='color:#111;'> 1.67MB </span>","children":null,"spread":false},{"title":"11-XGBoost.pdf <span style='color:#111;'> 2.36MB </span>","children":null,"spread":false}],"spread":false}],"spread":true}]