【文件属性】:
文件名称:data-analysis:数据分析
文件大小:1.2MB
文件格式:ZIP
更新时间:2021-04-05 23:22:30
JupyterNotebook
数据分析
基本数据分析样本文件
逻辑回归
线性回归
聚类
随机森林分类
├── README.md
├── clustering
│ ├── clustering.py
│ └── requirements.txt
├── linear-regression
│ ├── linear-regression.py
│ └── requirements.txt
├── logistic-regression
│ ├── logistic-regression.py
│ └── requirements.txt
└── random_forest
└── random_forest_classifier.py
【文件预览】:
data-analysis-master
----deep-learning()
--------ann.py(3KB)
--------cnn.py(2KB)
----.gitignore(2KB)
----reinforcement()
--------upper-confidence.py(1KB)
--------thompson.py(1KB)
----README.md(517B)
----.github()
--------workflows()
----linear-regression()
--------linear-regression.py(2KB)
--------multiple-linear-regression.py(1KB)
--------random-forest-regression.py(882B)
--------svr.py(1KB)
--------requirements.txt(14B)
--------decision-tree-regression.py(861B)
--------lr.py(1KB)
--------polynomial-regression.py(2KB)
----class_method()
--------customer.py(924B)
--------demo.py(5KB)
----NLP()
--------nlp.py(2KB)
----python-note()
--------a_demo.py(1KB)
--------gc.py(183B)
--------Student.py(446B)
--------amazon_nlp.py(3KB)
--------weblazada()
--------webscrapper.py(2KB)
--------py-note.py(2KB)
--------b_demo.py(2KB)
--------twitterapi.py(2KB)
--------web-sel.py(3KB)
--------pytest.py(1KB)
--------flask.py(2KB)
--------app1.py(398B)
--------scrapeair.py(1KB)
--------demo_python.py(3KB)
--------basicpython.py(1KB)
--------scrapewiki.py(2KB)
--------gender_flask.py(1KB)
--------web-selenium.py(7KB)
----sql()
--------script.sql(10KB)
----random_forest()
--------random_forest_classifier.py(3KB)
----association-rule()
--------apriori.py(1KB)
----logistic-regression()
--------random-forest-classification.py(3KB)
--------svm.py(3KB)
--------decision-tree.py(3KB)
--------logistic.py(3KB)
--------requirements.txt(14B)
--------kernel-svm.py(3KB)
--------logistic-regression.py(4KB)
--------knn.py(3KB)
--------naive-bayes.py(3KB)
----jupyter-notebook()
--------flights.ipynb(1.67MB)
----docker-python()
--------Dockerfile(160B)
--------app.py(113B)
--------requirements.txt(8B)
----clustering()
--------hierarchical.py(1KB)
--------clustering.py(1KB)
--------requirements.txt(14B)
--------kmeans.py(1KB)
--------knn.py(1KB)