Machine-Learning-A-Z-Datasets:udemy的机器学习AZ课程中的所有Python和R源材料-Sour...
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2021-03-24
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Machine-Learning-A-Z-Datasets-master.zip （94个子文件） 
Machine-Learning-A-Z-Datasets-master Part 10 - Model Selection & Boosting Data 
Social_Network_Ads.csv 11KB Churn_Modelling.csv 669KB 1 - Model Selection k_fold_cross_validation.py 3KB grid_search.R 3KB grid_search.py 3KB k_fold_cross_validation.R 3KB 2 - XGBoost xgboost.py 1KB xgboost.R 2KB README.md 103B Part 6 - Reinforcement Learning Slides 
Thompson_Sampling.png 1.18MB UCB_Algorithm.png 1.22MB Data Ads_CTR_Optimisation.csv 205KB 2 - Thompson Sampling thompson_sampling.R 1004B thompson_sampling.py 1KB 1 - Upper Confidence Bound (UCB) upper_confidence_bound.R 1KB upper_confidence_bound.py 1KB Template random_selection.R 511B random_selection.py 616B Part 1 - Data Preprocessing Data Data.csv 226B missing data missing_data.R 435B missing_data.py 457B categorial data categorical_data.py 869B categorical_data.R 762B Template template.py 685B template.R 446B Part 9 - Dimensionality Reduction 3 - Kernel PCA kernel_pca.py 3KB kernel_pca.R 3KB Data Wine.csv 11KB Social_Network_Ads.csv 11KB 2 - Linear Discriminant Analysis (LDA) lda.py 3KB lda.R 2KB 1 - Principal Component Analysis (PCA) pca.R 3KB pca.py 3KB .gitattributes 112B Part 3 - Classification 2 - K-Nearest Neighbors (K-NN) knn.R 2KB knn.py 3KB Slides 
Classification-Pros-Cons.pdf 29KB 4 - Kernel SVM kernel_svm.py 3KB kernel_svm.R 2KB Data Social_Network_Ads.csv 11KB 5 - Naive Bayes naive_bayes.py 3KB naive_bayes.R 2KB 3 - Support Vector Machine (SVM) svm.py 3KB svm.R 2KB 1 - Logistic Regression logistic_regression.R 2KB logistic_regression.py 3KB 7 - Random Forest Classification random_forest_classification.R 2KB random_forest_classification.py 3KB 6 - Decision Tree Classification decision_tree_classification.R 2KB decision_tree_classification.py 3KB Template classification_template.R 2KB classification_template.py 2KB Part 8 - Deep Learning Slides Stochastic_Gradient_Descent.png 1.38MB 1 - Artificial Neural Networks (ANN) ann.py 2KB ann.R 1KB Data 
cnn.zip 134B Churn_Modelling.csv 669KB 2 - Convolutional Neural Networks (CNN) cnn.py 2KB Part 7 - Natural Language Processing Data Restaurant_Reviews.tsv 60KB 1 - Natural Language Processing natural_language_processing.py 1KB natural_language_processing.R 2KB Part 5 - Association Rule Learning Data Market_Basket_Optimisation.csv 296KB 1 - Apriori R apriori.R 482B Python apyori.py 14KB apriori.py 531B 2 - Eclat eclat.R 457B Part 4 - Clustering Slides Clustering-Pros-Cons.pdf 26KB Data Mall_Customers.csv 4KB 2 - Hierarchical Clustering hc.py 2KB hc.R 1KB 1 - K-Means Clustering kmeans.R 1KB kmeans.py 2KB Part 2 - Regression 3 - Polynomial Regression polynomial_regression.R 3KB polynomial_regression.py 2KB Slides Step-by-step-Blueprints-For-Building-Models.pdf 769KB Regression-Pros-Cons.pdf 27KB Regularization.pdf 199KB 4 - Support Vector Regression (SVR) svr.R 2KB svr.py 1KB 6 - Random Forest Regression random_forest_regression.py 1KB random_forest_regression.R 1KB Data Position_Salaries.csv 246B Salary_Data.csv 454B 50_Startups.csv 2KB 2 - Multiple Linear Regression multiple_linear_regression.py 1KB homework solutions multiple_linear_regression.py 2KB multiple_linear_regression.R 2KB multiple_linear_regression.R 838B 5 - Decision Tree Regression decision_tree_regression.R 1KB decision_tree_regression.py 1KB Template regression_template.py 1KB regression_template.R 1KB 1 - Simple Linear Regression simple_linear_regression.py 1KB simple_linear_regression.R 1KB
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