文件名称：MachineLearning_Pythone
文件大小：881KB
文件格式：ZIP
更新时间：2024-03-14 05:35:57
JupyterNotebook
MachineLearning_Pythone
【文件预览】：
MachineLearning_Pythone-master
----K-Means Clustering.ipynb(18KB)
----Untitled.ipynb(6KB)
----mergedData.csv(230KB)
----middleResult.csv(534KB)
----4-2. Usecase_ScikitLearn (Supervised Classification_SVM)_CJ.ipynb(13KB)
----Classification.ipynb(16KB)
----4-5. Usecase_TS_model - R.ipynb(109KB)
----4-4- Usecase_TF_Tensorflow_Keras_Linear-ver2019.ipynb(232KB)
----4-3. Usecase_ScikitLearn (UnSupervised Learning)(학생분류)_CJ.ipynb(18KB)
----이형섭 머신러닝 과제.ipynb(108KB)
----데이터 총정리.ipynb(94KB)
----Decision Tree Classifier.ipynb(10KB)
----4-4. Usecase_TF_Tensorflow_Keras_Class-ver2019.ipynb(456KB)
----대량 데이터 적용해보기.ipynb(54KB)
----데이터 조작하기.ipynb(146KB)
----.ipynb_checkpoints()
--------대량 데이터 적용해보기-checkpoint.ipynb(54KB)
--------4-1. Usecase_ScikitLearn(Supervised Regression_Decision)_빅데이터이해 및 머신러닝-CJ-checkpoint.ipynb(128KB)
--------이형섭 머신러닝 과제-checkpoint.ipynb(108KB)
--------머신러닝-checkpoint.ipynb(92KB)
--------K-Means Clustering-checkpoint.ipynb(72B)
--------Decision Tree Classifier-checkpoint.ipynb(6KB)
--------Untitled-checkpoint.ipynb(6KB)
--------데이터 총정리-checkpoint.ipynb(94KB)
--------데이터 분석(데이터 변화 적용)-checkpoint.ipynb(21KB)
--------Classification-checkpoint.ipynb(16KB)
----데이터 분석(데이터 변화 적용).ipynb(21KB)
----머신러닝.ipynb(92KB)
----4-1. Usecase_ScikitLearn(Supervised Regression_Decision)_빅데이터이해 및 머신러닝-CJ.ipynb(128KB)