├── KNN ├── KNN.ipynb ├── KNN_solution.ipynb └── utils.py ├── ML_in_practice ├── .DS_Store ├── End_to_end_example.ipynb ├── End_to_end_example_solution.ipynb ├── ProjectHelper.ipynb ├── clean_titanic_data.csv ├── preprocessed_titanic_data.csv ├── test.csv └── titanic.csv ├── classification_model_performance ├── classification_model_performance.ipynb ├── classification_model_performance_solution.ipynb └── preprocessed_titanic_data.csv ├── decision_trees ├── decision_trees.ipynb ├── decision_trees_solution.ipynb ├── random_forest.ipynb ├── random_forest_solution.ipynb └── utils.py ├── ensemble_methods ├── AdaBoost.ipynb ├── AdaBoost_solution.ipynb ├── XGBoost.ipynb ├── XGBoost_solution.ipynb └── utils.py ├── linear_regression ├── Coding_linear_regression.ipynb ├── Coding_linear_regression_solution.ipynb └── utils.py ├── logistic_regression ├── Coding_logistic_regression.ipynb ├── Coding_logistic_regression_solution.ipynb └── utils.py ├── perceptron_algorithm ├── Coding_perceptron_algorithm.ipynb ├── Coding_perceptron_algorithm_solution.ipynb └── utils.py ├── polynomial_regression ├── Polynomial_regression_regularization.ipynb └── Polynomial_regression_regularization_solution.ipynb └── support_vector_machines ├── SVM_coding.ipynb ├── SVM_coding_solution.ipynb ├── linear.csv ├── one_circle.csv ├── two_circles.csv └── utils.py /KNN/KNN.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/KNN/KNN.ipynb -------------------------------------------------------------------------------- /KNN/KNN_solution.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/KNN/KNN_solution.ipynb -------------------------------------------------------------------------------- /KNN/utils.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/KNN/utils.py -------------------------------------------------------------------------------- /ML_in_practice/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/ML_in_practice/.DS_Store -------------------------------------------------------------------------------- /ML_in_practice/End_to_end_example.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/ML_in_practice/End_to_end_example.ipynb -------------------------------------------------------------------------------- /ML_in_practice/End_to_end_example_solution.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/ML_in_practice/End_to_end_example_solution.ipynb -------------------------------------------------------------------------------- /ML_in_practice/ProjectHelper.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/ML_in_practice/ProjectHelper.ipynb -------------------------------------------------------------------------------- /ML_in_practice/clean_titanic_data.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/ML_in_practice/clean_titanic_data.csv -------------------------------------------------------------------------------- /ML_in_practice/preprocessed_titanic_data.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/ML_in_practice/preprocessed_titanic_data.csv -------------------------------------------------------------------------------- /ML_in_practice/test.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/ML_in_practice/test.csv -------------------------------------------------------------------------------- /ML_in_practice/titanic.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/ML_in_practice/titanic.csv -------------------------------------------------------------------------------- /classification_model_performance/classification_model_performance.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/classification_model_performance/classification_model_performance.ipynb -------------------------------------------------------------------------------- /classification_model_performance/classification_model_performance_solution.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/classification_model_performance/classification_model_performance_solution.ipynb -------------------------------------------------------------------------------- /classification_model_performance/preprocessed_titanic_data.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/classification_model_performance/preprocessed_titanic_data.csv -------------------------------------------------------------------------------- /decision_trees/decision_trees.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/decision_trees/decision_trees.ipynb -------------------------------------------------------------------------------- /decision_trees/decision_trees_solution.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/decision_trees/decision_trees_solution.ipynb -------------------------------------------------------------------------------- /decision_trees/random_forest.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/decision_trees/random_forest.ipynb -------------------------------------------------------------------------------- /decision_trees/random_forest_solution.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/decision_trees/random_forest_solution.ipynb -------------------------------------------------------------------------------- /decision_trees/utils.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/decision_trees/utils.py -------------------------------------------------------------------------------- /ensemble_methods/AdaBoost.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/ensemble_methods/AdaBoost.ipynb -------------------------------------------------------------------------------- /ensemble_methods/AdaBoost_solution.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/ensemble_methods/AdaBoost_solution.ipynb -------------------------------------------------------------------------------- /ensemble_methods/XGBoost.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/ensemble_methods/XGBoost.ipynb -------------------------------------------------------------------------------- /ensemble_methods/XGBoost_solution.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/ensemble_methods/XGBoost_solution.ipynb -------------------------------------------------------------------------------- /ensemble_methods/utils.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/ensemble_methods/utils.py -------------------------------------------------------------------------------- /linear_regression/Coding_linear_regression.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/linear_regression/Coding_linear_regression.ipynb -------------------------------------------------------------------------------- /linear_regression/Coding_linear_regression_solution.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/linear_regression/Coding_linear_regression_solution.ipynb -------------------------------------------------------------------------------- /linear_regression/utils.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/linear_regression/utils.py -------------------------------------------------------------------------------- /logistic_regression/Coding_logistic_regression.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/logistic_regression/Coding_logistic_regression.ipynb -------------------------------------------------------------------------------- /logistic_regression/Coding_logistic_regression_solution.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/logistic_regression/Coding_logistic_regression_solution.ipynb -------------------------------------------------------------------------------- /logistic_regression/utils.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/logistic_regression/utils.py -------------------------------------------------------------------------------- /perceptron_algorithm/Coding_perceptron_algorithm.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/perceptron_algorithm/Coding_perceptron_algorithm.ipynb -------------------------------------------------------------------------------- /perceptron_algorithm/Coding_perceptron_algorithm_solution.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/perceptron_algorithm/Coding_perceptron_algorithm_solution.ipynb -------------------------------------------------------------------------------- /perceptron_algorithm/utils.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/perceptron_algorithm/utils.py -------------------------------------------------------------------------------- /polynomial_regression/Polynomial_regression_regularization.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/polynomial_regression/Polynomial_regression_regularization.ipynb -------------------------------------------------------------------------------- /polynomial_regression/Polynomial_regression_regularization_solution.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/polynomial_regression/Polynomial_regression_regularization_solution.ipynb -------------------------------------------------------------------------------- /support_vector_machines/SVM_coding.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/support_vector_machines/SVM_coding.ipynb -------------------------------------------------------------------------------- /support_vector_machines/SVM_coding_solution.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/support_vector_machines/SVM_coding_solution.ipynb -------------------------------------------------------------------------------- /support_vector_machines/linear.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/support_vector_machines/linear.csv -------------------------------------------------------------------------------- /support_vector_machines/one_circle.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/support_vector_machines/one_circle.csv -------------------------------------------------------------------------------- /support_vector_machines/two_circles.csv: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/support_vector_machines/two_circles.csv -------------------------------------------------------------------------------- /support_vector_machines/utils.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/s7s/machine_learning_1/HEAD/support_vector_machines/utils.py --------------------------------------------------------------------------------