# ML-code-100days

**Repository Path**: yan_feitian/ML-code-100days

## Basic Information

- **Project Name**: ML-code-100days
- **Description**: 100天机器学习 （翻译+ 实操）
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 1
- **Created**: 2020-06-24
- **Last Updated**: 2022-04-20

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# 100days-ML-code（翻译+ 实操）
## 1 原文----[Avik-jain/100-days-of-ML](https://github.com/Avik-Jain/100-Days-Of-ML-Code)
## 2 翻译汉化项目----[MachineLearning100/100-Days-Of-ML-Code](https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/README.md)
> ps:个人认为：谷歌翻译水平，无详细注释讲解，仅仅适合参考或者快食。


* Tip🌟 ：如果下面 ipynb 文件打开速度过慢或者打不开，可以将文件链接复制到 https://nbviewer.jupyter.org/ 进行打开
-----------------

## 1. [Day1---Data preprocessing](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day1_Data_preprocessing/README.md)
## [code](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day1_Data_preprocessing/Data_preprocessing.py)
![](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day1_Data_preprocessing/Day%201.jpg)

--------

## 2. [Day2---Simple linear regression](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day2_SImple_Linear_regression/README.md)
## [code](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day2_SImple_Linear_regression/Simple_linear_regression.py)
![](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day2_SImple_Linear_regression/Day%202.jpg)

-----------

## 3. [Day3---Multiple linear regression](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day3_Multiple_Linear_regression/README.md)
## [code](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day3_Multiple_Linear_regression/Multiple_Linear_regression.py)
![](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day3_Multiple_Linear_regression/Day%203.jpg)

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## 4. [Day4+Day5+Day6---Logistic regression](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day4-5-6_Logistic_regression/README.md)
## [code](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day4-5-6_Logistic_regression/logistic_regression.py)
![](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day4-5-6_Logistic_regression/Day%204.jpg)

---------



## 5. [Day7-8-9-10---KNN](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day7-8-9-10KNN/README.md)
## [code](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day7-8-9-10KNN/KNN.py)

![](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day7-8-9-10KNN/Day%207.jpg)


----

## 6. [Day 11-12-13-14---SVM](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day11-12-13-14_SVM/README.md)
## [code](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day11-12-13-14_SVM/SVM%20%E5%AE%9E%E7%8E%B0.ipynb)
![](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day11-12-13-14_SVM/Day%2012.jpg)

---

## 7. Day 15-16-17 --- Data Visualization
#### 1.  [Data Visualization by  Pandas(matplotlib)](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day15-16-17_Data%20Visualization/Data_visualization_by_pandas.ipynb)

![](http://pqvlt7eed.bkt.clouddn.com/d0290.png)

#### 2. [Data Visualization by  Seaborn](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day15-16-17_Data%20Visualization/Data%20Visualization%20by%20Seaborn.ipynb)
![](http://pqvlt7eed.bkt.clouddn.com/m7gn8.png)

#### 3. [Time series data Visualization](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day15-16-17_Data%20Visualization/Time_series_data_Visualization.ipynb)

![](http://pqvlt7eed.bkt.clouddn.com/m2x6t.png)

----

## 8. Day 18-19-20 --- Linear Algebra

* [线性代数基础知识快速学习回顾](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day%2018-19-20%20Linear%20algebra/%E7%BA%BF%E6%80%A7%E4%BB%A3%E6%95%B0%E5%9F%BA%E7%A1%80%E7%9F%A5%E8%AF%86.pdf)

* 笔记内容为 [3blue1brown 线性代数系列视频课程](https://space.bilibili.com/88461692?from=search&seid=6764604302374459112)学习记录。

* 文档没有添加目录，因为内容不多,建议按照顺序阅读，便于理解。

-----

## 8. Day 21-22-23 --- Probability and Mathematical Statistics


* [概率论基础知识快速学习回顾](https://github.com/LiuChuang0059/100days-ML-code/blob/master/Day21-22-23_Probability/Probability_and_Mathematical_Statistics_1.pdf)


* 本篇笔记主要是概率论相关知识学习，数理统计相关在下一篇。

* 主要参考：

	 _《概率论与数理统计》齐民友, 武汉大学_

	 _《Probability and Statistics》Morris H. DeGroot , Carnegie Mellon
University_