[{"title":"( 44 个子文件 2.12MB ) 【机器学习学习资料】机器学习:公式推导与代码实现(附代码+数据).zip","children":[{"title":"Machine_Learning_Code_Implementation-master","children":[{"title":"charpter17_kmeans","children":[{"title":"kmeans.ipynb <span style='color:#111;'> 7.14KB </span>","children":null,"spread":false}],"spread":true},{"title":"charpter18_PCA","children":[{"title":"pca.ipynb <span style='color:#111;'> 38.99KB </span>","children":null,"spread":false}],"spread":true},{"title":"charpter10_AdaBoost","children":[{"title":"adaboost.ipynb <span style='color:#111;'> 34.67KB </span>","children":null,"spread":false}],"spread":true},{"title":"pic","children":[{"title":"cover.jpg <span style='color:#111;'> 148.83KB </span>","children":null,"spread":false},{"title":"ml_xmind.png <span style='color:#111;'> 83.30KB </span>","children":null,"spread":false}],"spread":true},{"title":"charpter25_MCMC","children":[{"title":"mcmc.ipynb <span style='color:#111;'> 84.35KB </span>","children":null,"spread":false}],"spread":true},{"title":"charpter2_linear_regression","children":[{"title":"linear_regression.ipynb <span style='color:#111;'> 82.53KB </span>","children":null,"spread":false}],"spread":true},{"title":"charpter3_logistic_regression","children":[{"title":"logistic_regression.ipynb <span style='color:#111;'> 62.58KB </span>","children":null,"spread":false}],"spread":true},{"title":"charpter11_GBDT","children":[{"title":"utils.py <span style='color:#111;'> 909B </span>","children":null,"spread":false},{"title":"gbdt.ipynb <span style='color:#111;'> 8.09KB </span>","children":null,"spread":false},{"title":"cart.py <span style='color:#111;'> 7.16KB </span>","children":null,"spread":false}],"spread":true},{"title":"charpter5_LDA","children":[{"title":"LDA.ipynb <span style='color:#111;'> 21.04KB </span>","children":null,"spread":false}],"spread":true},{"title":"charpter24_CRF","children":[{"title":"crf.ipynb <span style='color:#111;'> 8.74KB </span>","children":null,"spread":false}],"spread":true},{"title":"charpter12_XGBoost","children":[{"title":"utils.py <span style='color:#111;'> 1.10KB </span>","children":null,"spread":false},{"title":"xgboost.ipynb <span style='color:#111;'> 20.22KB </span>","children":null,"spread":false},{"title":"cart.py <span style='color:#111;'> 7.12KB </span>","children":null,"spread":false}],"spread":true},{"title":"charpter23_HMM","children":[{"title":"hmm.ipynb <span style='color:#111;'> 5.41KB </span>","children":null,"spread":false}],"spread":true},{"title":"charpter21_Bayesian_models","children":[{"title":"naive_bayes.ipynb <span style='color:#111;'> 6.62KB </span>","children":null,"spread":false},{"title":"bayesian_network.ipynb <span style='color:#111;'> 5.03KB </span>","children":null,"spread":false}],"spread":true},{"title":"charpter1_ml_start","children":[{"title":"NumPy_sklearn.ipynb <span style='color:#111;'> 19.28KB </span>","children":null,"spread":false}],"spread":false},{"title":"charpter15_random_forest","children":[{"title":"random_forest.ipynb <span style='color:#111;'> 12.18KB </span>","children":null,"spread":false},{"title":"cart.py <span style='color:#111;'> 7.12KB </span>","children":null,"spread":false}],"spread":false},{"title":"charpter22_EM","children":[{"title":"em.ipynb <span style='color:#111;'> 4.46KB </span>","children":null,"spread":false}],"spread":false},{"title":"charpter19_SVD","children":[{"title":"louwill.jpg <span style='color:#111;'> 458.51KB </span>","children":null,"spread":false},{"title":"svd.ipynb <span style='color:#111;'> 6.83KB </span>","children":null,"spread":false}],"spread":false},{"title":"charpter8_neural_networks","children":[{"title":"neural_networks.ipynb <span style='color:#111;'> 376.17KB </span>","children":null,"spread":false},{"title":"perceptron.py <span style='color:#111;'> 1.12KB </span>","children":null,"spread":false},{"title":"perceptron.ipynb <span style='color:#111;'> 38.66KB </span>","children":null,"spread":false}],"spread":false},{"title":"charpter6_knn","children":[{"title":"knn.ipynb <span style='color:#111;'> 60.89KB </span>","children":null,"spread":false}],"spread":false},{"title":"charpter20_MEM","children":[{"title":"max_entropy_model.ipynb <span style='color:#111;'> 10.04KB </span>","children":null,"spread":false}],"spread":false},{"title":"charpter7_decision_tree","children":[{"title":"example_data.csv <span style='color:#111;'> 423B </span>","children":null,"spread":false},{"title":"utils.py <span style='color:#111;'> 750B </span>","children":null,"spread":false},{"title":"ID3.ipynb <span style='color:#111;'> 42.33KB </span>","children":null,"spread":false},{"title":"CART.ipynb <span style='color:#111;'> 12.27KB </span>","children":null,"spread":false}],"spread":false},{"title":"charpter9_SVM","children":[{"title":"soft_margin_svm.ipynb <span style='color:#111;'> 67.71KB </span>","children":null,"spread":false},{"title":"hard_margin_svm.ipynb <span style='color:#111;'> 70.68KB </span>","children":null,"spread":false},{"title":"non-linear_svm.ipynb <span style='color:#111;'> 60.83KB </span>","children":null,"spread":false}],"spread":false},{"title":"charpter13_LightGBM","children":[{"title":"lightgbm.ipynb <span style='color:#111;'> 15.59KB </span>","children":null,"spread":false}],"spread":false},{"title":"charpter16_ensemble_compare","children":[{"title":"compare_and_tuning.ipynb <span style='color:#111;'> 69.82KB </span>","children":null,"spread":false}],"spread":false},{"title":"charpter14_CatBoost","children":[{"title":"adult.data <span style='color:#111;'> 3.79MB </span>","children":null,"spread":false},{"title":"catboost.ipynb <span style='color:#111;'> 1.21MB </span>","children":null,"spread":false}],"spread":false},{"title":"charpter4_regression_expansion","children":[{"title":"lasso.ipynb <span style='color:#111;'> 42.34KB </span>","children":null,"spread":false},{"title":"example.dat <span style='color:#111;'> 84.71KB </span>","children":null,"spread":false},{"title":"ridge.ipynb <span style='color:#111;'> 37.20KB </span>","children":null,"spread":false}],"spread":false}],"spread":false}],"spread":true}]