GitHub - ancestor9/2020_seminar: 2020.9 데이터솔루션 1일차 강의 세미나 자료

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2020.9 데이터솔루션 1일차 강의 세미나 자료

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Name		Name	Last commit message	Last commit date
Latest commit History 9 Commits
notebooks		notebooks
01_request.ipynb		01_request.ipynb
1203_06_fastapi_iris_client.ipynb		1203_06_fastapi_iris_client.ipynb
20201022_00_comments.ipynb		20201022_00_comments.ipynb
20201022_02_KNN.ipynb		20201022_02_KNN.ipynb
20201022_03_GNB_LGR.ipynb		20201022_03_GNB_LGR.ipynb
20201022_04_SVC_DT.ipynb		20201022_04_SVC_DT.ipynb
20201022_05_Ensemble .ipynb		20201022_05_Ensemble .ipynb
20201022_06_Smote.ipynb		20201022_06_Smote.ipynb
20201022_model_comparison_feature_extraction.ipynb		20201022_model_comparison_feature_extraction.ipynb
202103_01_Setup.ipynb		202103_01_Setup.ipynb
Capstone_Design_01_rocket_launch_simple_version.ipynb		Capstone_Design_01_rocket_launch_simple_version.ipynb
Ch_05_BOW_기반의_문서분류.ipynb		Ch_05_BOW_기반의_문서분류.ipynb
Python_데이터과학_2일차.pptx		Python_데이터과학_2일차.pptx
Python_데이터과학_2일차_제본용.pptx		Python_데이터과학_2일차_제본용.pptx
Python_데이터과학_머신러닝_1일차_제본용.pptx		Python_데이터과학_머신러닝_1일차_제본용.pptx
Python_데이터과학_머신러닝_20201022.pptx		Python_데이터과학_머신러닝_20201022.pptx
Python_데이터과학_머신러닝_2021.pptx		Python_데이터과학_머신러닝_2021.pptx
RAG_with_Ko_PlatYi_6B.ipynb		RAG_with_Ko_PlatYi_6B.ipynb
SHAP.ipynb		SHAP.ipynb
basic-semi-supervised-learning-models.ipynb		basic-semi-supervised-learning-models.ipynb
lab_1_1_getting started for scikit-learn machine learning.ipynb		lab_1_1_getting started for scikit-learn machine learning.ipynb
lab_1_2_model evaluation.ipynb		lab_1_2_model evaluation.ipynb
lab_1_3_imbalance data.ipynb		lab_1_3_imbalance data.ipynb
lab_2_1_Nearest Neighbors.ipynb		lab_2_1_Nearest Neighbors.ipynb
lab_2_2_Logistic regression.ipynb		lab_2_2_Logistic regression.ipynb
lab_2_3 & 3_1_SGD MLP.ipynb		lab_2_3 & 3_1_SGD MLP.ipynb
lab_3_2_gaussianNB with text mining.ipynb		lab_3_2_gaussianNB with text mining.ipynb
lab_3_3_svm.ipynb		lab_3_3_svm.ipynb
lab_3_3_svm_hyperparameters.ipynb		lab_3_3_svm_hyperparameters.ipynb
lab_4_dt_ensemble.ipynb		lab_4_dt_ensemble.ipynb
lab_4_실습코드.ipynb		lab_4_실습코드.ipynb
lab_5_1_Multiclass and multioutput algorithms.ipynb		lab_5_1_Multiclass and multioutput algorithms.ipynb
lab_5_2_pycaret & interpretability.ipynb		lab_5_2_pycaret & interpretability.ipynb
lab_5_3_model agnostic interpretability (eXAI).ipynb		lab_5_3_model agnostic interpretability (eXAI).ipynb
lab_6_1_feature selection methods.ipynb		lab_6_1_feature selection methods.ipynb
lab_6_2_Boruta_algorithm.ipynb		lab_6_2_Boruta_algorithm.ipynb
lab_6_2_genetic algorithm.ipynb		lab_6_2_genetic algorithm.ipynb
lab_6_3_PCA.ipynb		lab_6_3_PCA.ipynb
lab_6_실습코드_fashion minst classification with pca.ipynb		lab_6_실습코드_fashion minst classification with pca.ipynb
lab_7_1_Imbalance.ipynb		lab_7_1_Imbalance.ipynb
lab_7_2_Imbalanced data handling.ipynb		lab_7_2_Imbalanced data handling.ipynb
lab_7_실습코드_AV_Agriculture_Random_Forest_with_SMOTE.ipynb		lab_7_실습코드_AV_Agriculture_Random_Forest_with_SMOTE.ipynb
lab_8_1_clustering methods.ipynb		lab_8_1_clustering methods.ipynb
lab_8_2_anomaly_detection.ipynb		lab_8_2_anomaly_detection.ipynb
lab_8_실습코드_imbalance_Ensemble_Clustering_anomaly models.ipynb		lab_8_실습코드_imbalance_Ensemble_Clustering_anomaly models.ipynb
regression_sample.xlsx		regression_sample.xlsx
semi_supervised_learning.ipynb		semi_supervised_learning.ipynb
statistics_01.ipynb		statistics_01.ipynb
실습_연습.ipynb		실습_연습.ipynb
실습_정답.ipynb		실습_정답.ipynb