# PythonStudyNote

**Repository Path**: debuggerCaofanCPU/PythonStudyNote

## Basic Information

- **Project Name**: PythonStudyNote
- **Description**: Use Python to touch BigData, MachineLearning and ArtificialIntelligence
- **Primary Language**: Python
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-09-01
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# [PythonStudyNote](https://github.com/caofanCPU/PythonStudyNote)
Use Python to touch BigData, MachineLearning and ArtificialIntelligence.
## Version 1.2	
**`DateTime`**  
{  
    import time  
    print(time.strftime('%Y-%m-%d %H:%M:%S',  
       time.localtime(time.time())))  
}
***
## Components
- **PythonBase**
- **MachineLearning**
- **KiggleContest**
***
### PythonBase
* list
* array
* dataframe
* modules&packages(os, numpy, pandas, sklearn etc.)
### MachineLearning
* [Prediction of Benign/malignant tumor](https://github.com/caofanCPU/PythonStudyNote/blob/master/MachineLearning&KaggleContest/ML1全套/乳腺癌肿瘤预测_简单版_完整代码.py)(良性/恶性肿瘤预测)
* [Handwritten numeral recognition of postal system](https://github.com/caofanCPU/PythonStudyNote/tree/master/MachineLearning&KaggleContest/ML2全套/手写体原始数字图片经PCA算法处理后的二维空间分布.py)(邮政系统手写体数字识别)
* [Survival possibility analysis for passengers of the Titanic](https://github.com/caofanCPU/PythonStudyNote/tree/master/MachineLearning&KaggleContest/ML2全套/坦坦尼克号沉船事故乘客生还可能性预测.py)(泰坦尼克号沉船事故乘客生还可能性分析)
* [Housing price of Boston](https://github.com/caofanCPU/PythonStudyNote/tree/master/MachineLearning&KaggleContest/ML3模型优化/skflow工具包_回归预测波斯顿房价.py)(波士顿房价预测)  
***  
## Highlights

![AfterPCA](http://i1.piimg.com/588926/a28673e13fc6f3dd.png)  

![Optdigits](http://i1.piimg.com/588926/1535a55c29dce308.png)   

![Cluster1](http://i1.piimg.com/588926/1ade74e673603440.png)  

![Cluster2](http://i1.piimg.com/588926/1ade74e673603440.png)  

![FeatureSelection](http://i2.muimg.com/588926/d05743693bed3b15.png)  

***
## Remarks
    For quickly starting Python, I recommend you to learn [**`python多叉树`**](https://github.com/caofanCPU/PythonStudyNote/tree/master/PythonQuickStart/python多叉树.py) and [**`python缓存模拟`**](https://github.com/caofanCPU/PythonStudyNote/tree/master/PythonQuickStart/python缓存模拟.py). However, it will be difficult to read the code before you know the background story. Reading *Remarks.txt* carefully until you can write some pseudo-code for solving problems.