Name	Name	Last commit message	Last commit date
Latest commit History 6 Commits
.ipynb_checkpoints	.ipynb_checkpoints
_build	_build
.DS_Store	.DS_Store
2-2-认识Jupyter-Notebook.ipynb	2-2-认识Jupyter-Notebook.ipynb
2-3-Python编程基础.ipynb	2-3-Python编程基础.ipynb
2-4-1-sample_data.csv	2-4-1-sample_data.csv
2-4-认识numpy与pandas.ipynb	2-4-认识numpy与pandas.ipynb
3-1-使用Python进行描述统计单变量.ipynb	3-1-使用Python进行描述统计单变量.ipynb
3-10-1-click_data.csv	3-10-1-click_data.csv
3-10-列联表检验.ipynb	3-10-列联表检验.ipynb
3-2-1-fish_multi.csv	3-2-1-fish_multi.csv
3-2-2-shoes.csv	3-2-2-shoes.csv
3-2-3-cov.csv	3-2-3-cov.csv
3-2-使用Python进行描述统计多变量.ipynb	3-2-使用Python进行描述统计多变量.ipynb
3-3-2-fish_multi_2.csv	3-3-2-fish_multi_2.csv
3-3-基于matplotlib-seaborn的数据可视化.ipynb	3-3-基于matplotlib-seaborn的数据可视化.ipynb
3-4-1-fish_length_100000.csv	3-4-1-fish_length_100000.csv
3-4-用Python模拟抽样.ipynb	3-4-用Python模拟抽样.ipynb
3-5-样本统计量的性质.ipynb	3-5-样本统计量的性质.ipynb
3-6-正态分布及其应用.ipynb	3-6-正态分布及其应用.ipynb
3-7-1-fish_length.csv	3-7-1-fish_length.csv
3-7-参数估计.ipynb	3-7-参数估计.ipynb
3-8-1-junk-food-weight.csv	3-8-1-junk-food-weight.csv
3-8-假设检验.ipynb	3-8-假设检验.ipynb
3-9-1-paired-t-test.csv	3-9-1-paired-t-test.csv
3-9-均值差的检验.ipynb	3-9-均值差的检验.ipynb
5-1-1-beer.csv	5-1-1-beer.csv
5-1-一元回归.ipynb	5-1-一元回归.ipynb
5-2-方差分析.ipynb	5-2-方差分析.ipynb
5-3-1-lm-model.csv	5-3-1-lm-model.csv
5-3-含有多个解释变量的模型.ipynb	5-3-含有多个解释变量的模型.ipynb
6-1-各种概率分布.ipynb	6-1-各种概率分布.ipynb
6-3-1-logistic-regression.csv	6-3-1-logistic-regression.csv
6-3-logistic回归.ipynb	6-3-logistic回归.ipynb
6-4-广义线性模型的评估.ipynb	6-4-广义线性模型的评估.ipynb
6-5-1-poisson-regression.csv	6-5-1-poisson-regression.csv
6-5-泊松回归.ipynb	6-5-泊松回归.ipynb
7-3-1-large-data.csv	7-3-1-large-data.csv
7-3-Python中的Ridge回归与Lasso回归.ipynb	7-3-Python中的Ridge回归与Lasso回归.ipynb
7-4-线性模型与神经网络.ipynb	7-4-线性模型与神经网络.ipynb
README.md	README.md
_config.yml	_config.yml
_toc.yml	_toc.yml
deploy.sh	deploy.sh

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6 Commits

.ipynb_checkpoints

_build

.DS_Store

2-2-认识Jupyter-Notebook.ipynb

2-3-Python编程基础.ipynb

2-4-1-sample_data.csv

2-4-认识numpy与pandas.ipynb

3-1-使用Python进行描述统计单变量.ipynb