Name	Name	Last commit message	Last commit date
Latest commit History 39 Commits
0_numpy_basic.ipynb	0_numpy_basic.ipynb
10_feature_scaling.ipynb	10_feature_scaling.ipynb
11_gradient_descent.ipynb	11_gradient_descent.ipynb
12_Linear Regression with Python_test.ipynb	12_Linear Regression with Python_test.ipynb
13_Linear Regression - Project Exercise .ipynb	13_Linear Regression - Project Exercise .ipynb
14_multiple_linear_regression_with_sklearn.ipynb	14_multiple_linear_regression_with_sklearn.ipynb
15_Logistic Regression with Python_test.ipynb	15_Logistic Regression with Python_test.ipynb
16_Logistic Regression Project Test.ipynb	16_Logistic Regression Project Test.ipynb
17_Logistic_Regression_with_sklearn.ipynb	17_Logistic_Regression_with_sklearn.ipynb
18_performance_metrics_for_classification_roc_curve.ipynb	18_performance_metrics_for_classification_roc_curve.ipynb
19.K Nearest Neighbors Project.ipynb	19.K Nearest Neighbors Project.ipynb
1_Pandas_basic.ipynb	1_Pandas_basic.ipynb
20_Decision Trees and Random Forests in Python - test.ipynb	20_Decision Trees and Random Forests in Python - test.ipynb
21_Decision Trees and Random Forest Project .ipynb	21_Decision Trees and Random Forest Project .ipynb
22_Decision Tree Titanic.ipynb	22_Decision Tree Titanic.ipynb
23_Support Vector Machines Project .ipynb	23_Support Vector Machines Project .ipynb
24_Support Vector Machines with Python(cancer).ipynb	24_Support Vector Machines with Python(cancer).ipynb
25_K Means Clustering with Python_1.ipynb	25_K Means Clustering with Python_1.ipynb
26_K Means Clustering Project .ipynb	26_K Means Clustering Project .ipynb
27_Clustering_excercise.ipynb	27_Clustering_excercise.ipynb
28_quiz_mammographic_masses.ipynb	28_quiz_mammographic_masses.ipynb
29_supervised-learning_exercise.ipynb	29_supervised-learning_exercise.ipynb
2_SF Salaries Exercise - self practice.ipynb	2_SF Salaries Exercise - self practice.ipynb
30_ensemble.ipynb	30_ensemble.ipynb
31_ensemble_exercise.ipynb	31_ensemble_exercise.ipynb
32_bagging_exercise.ipynb	32_bagging_exercise.ipynb
33_random_forest.ipynb	33_random_forest.ipynb
34_adaboost_exercise.ipynb	34_adaboost_exercise.ipynb
35_gradient_boosting_exercise.ipynb	35_gradient_boosting_exercise.ipynb
36_model-evaluation_exercise.ipynb	36_model-evaluation_exercise.ipynb
37_evaluation_exercise.ipynb	37_evaluation_exercise.ipynb
38_naive_bayes_total_exercise.ipynb	38_naive_bayes_total_exercise.ipynb
39_PCA(principal component analysis).ipynb	39_PCA(principal component analysis).ipynb
3_Ecommerce Purchases Exercise .ipynb	3_Ecommerce Purchases Exercise .ipynb
40_algorithm chains and pipelines.ipynb	40_algorithm chains and pipelines.ipynb
41_Breast_cancer_classification.ipynb	41_Breast_cancer_classification.ipynb
42_ML_Project_test.ipynb	42_ML_Project_test.ipynb
43_Text Preprocessing.ipynb	43_Text Preprocessing.ipynb
44_Text_Frequency Analysis.ipynb	44_Text_Frequency Analysis.ipynb
45_clustering_analysis.ipynb	45_clustering_analysis.ipynb
46_topic_model.ipynb	46_topic_model.ipynb
47_sentiment_analysis.ipynb	47_sentiment_analysis.ipynb
48_movie_review_sentiment_anal_test.ipynb	48_movie_review_sentiment_anal_test.ipynb
4_Basic of Python, Pandas and Matplotlib via analysis of CCTV in Seoul_answer_test.ipynb	4_Basic of Python, Pandas and Matplotlib via analysis of CCTV in Seoul_answer_test.ipynb
5_1 data_plot_test.ipynb	5_1 data_plot_test.ipynb
5_2 Visualization -Matplotlib_exercise.ipynb	5_2 Visualization -Matplotlib_exercise.ipynb
5_basic_plot_test.ipynb	5_basic_plot_test.ipynb
6_seaborn_plot_test.ipynb	6_seaborn_plot_test.ipynb
7_missing_value.ipynb	7_missing_value.ipynb
8_Pandas_plot.ipynb	8_Pandas_plot.ipynb
9_categorical_data.ipynb	9_categorical_data.ipynb
PCA(unsupervised learning).ipynb	PCA(unsupervised learning).ipynb
README.md	README.md
image.PNG	image.PNG

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Last commit message

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39 Commits

0_numpy_basic.ipynb

10_feature_scaling.ipynb

11_gradient_descent.ipynb

12_Linear Regression with Python_test.ipynb

13_Linear Regression - Project Exercise .ipynb

14_multiple_linear_regression_with_sklearn.ipynb

15_Logistic Regression with Python_test.ipynb

16_Logistic Regression Project Test.ipynb