# 机器学习算法和教程汇总

**Repository Path**: chaked/algorithm

## Basic Information

- **Project Name**: 机器学习算法和教程汇总
- **Description**: No description available
- **Primary Language**: Python
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2021-04-10
- **Last Updated**: 2023-06-03

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# 机器学习算法和教程汇总

#### 时间序列预测

[AAAI 2021最佳论文Informer：最强最快的序列预测神器](https://mp.weixin.qq.com/s/PqfRD8YsKHVVDNRUt0zrmw) | [论文](https://arxiv.org/abs/2012.07436) | [github](http://https://github.com/zhouhaoyi/Informer2020)

[Fbprophet](https://facebook.github.io/prophet/docs/quick_start.html) | [github](https://github.com/facebook/prophet)

[用Jupyter Notebook翻译Facebook时序分析工具prophet的官方文档](https://zhuanlan.zhihu.com/p/78116520)

[基于节假日因素的多尺度犯罪时序预测方法研究](https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&filename=GOAN202003012&dbname=CJFDLAST2020)

[基于改进粒子群IPSO与LSTM的短期电力负荷预测](https://blog.csdn.net/qq_41043389/article/details/103765363)

[Time Series Prediction Using LSTM Deep Neural Networks](https://www.altumintelligence.com/articles/a/Time-Series-Prediction-Using-LSTM-Deep-Neural-Networks)

[LSTM Neural Network for Time Series Prediction](https://www.jakob-aungiers.com/articles/a/LSTM-Neural-Network-for-Time-Series-Prediction)

[数据科学 | 手把手教你搭建一个LSTM时序模型](https://mp.weixin.qq.com/s?__biz=Mzg2MTA0NzA0Mw==&mid=2247490498&idx=1&sn=18824b0f7d9e978be95080b65c14b1e7&chksm=ce1c4baef96bc2b85fee45aa675ee448e3869b1f06173f0fdb2284cc85d6e36b0fafcfe3508e&mpshare=1&scene=1&srcid=&sharer_sharetime=1573352450805&sharer_shareid=f38583e798e3342517b16db300959868#rd)

[pmdarima: ARIMA estimators for Python](https://alkaline-ml.com/pmdarima/index.html#)

[Build High Performance Time Series Models using Auto ARIMA](https://www.analyticsvidhya.com/blog/2018/08/auto-arima-time-series-modeling-python-r/)



#### SVM

[LIBSVM -- A Library for Support Vector Machines](http://https://www.csie.ntu.edu.tw/~cjlin/libsvm/) | [github](https://github.com/cjlin1/libsvm)

[LibSVM学习3:一个实例搞定libsvm分类](https://blog.csdn.net/weixin_39789399/article/details/111519044)

[【LIBSVM】基于群智能优化算法的支持向量机 (SVM) 参数优化](https://zhuanlan.zhihu.com/p/143395096)

[【分类战车SVM】附录：用Python做SVM模型](https://mp.weixin.qq.com/s?__biz=MjM5MDEzNDAyNQ==&mid=207384849&idx=7&sn=eda3ef452c5b07cf741e8e01e813a516&mpshare=1&scene=1&srcid=0303kbsJvTL4gWw7e5aXFVI9#rd)

[机器学习之分类算法：SVM [6. LibSVM详解]](http://https://mp.weixin.qq.com/s?__biz=MzI2NDEwNzgxMw==&mid=402115576&idx=1&sn=68d4714631a3bc74bc95b8b06d280969&mpshare=1&scene=24&srcid=0724u0Rp6kMPHth5qYGt429Z#rd)

[LIBSVM回归详细操作步骤(附图)－－更新至20090806](http://blog.sina.com.cn/s/blog_5980835e0100drwx.html)

[支持向量机通俗导论（理解SVM的三层境界）](https://blog.csdn.net/v_july_v/article/details/7624837) | [文档](https://pan.baidu.com/s/1eQrgiOU)

[支持向量数据描述（SVDD）](https://zhuanlan.zhihu.com/p/97522759)

[用进化算法来优化SVM的参数C和Gamma——利用SCOOP库进行分布式加速计算](https://blog.csdn.net/sinat_23971513/article/details/105360791)



#### 朴素贝叶斯
[用scikit-learn实现朴素贝叶斯分类器](https://segmentfault.com/a/1190000002472791)

[scikit-learn 朴素贝叶斯类库使用小结](https://www.cnblogs.com/pinard/p/6074222.html)



#### 聚类

[利用层次聚类算法进行基于基站定位数据的商圈分析](https://mp.weixin.qq.com/s?__biz=MzAxMjUyNDQ5OA==&mid=2653557145&idx=1&sn=194fde7fce9ec8745a281fbda59d1b05&chksm=806e3f24b719b63225fa9fa8dda1c1008c56fac370a11cf1fec261b07125c83d90cbe47a7f2b&mpshare=1&scene=1&srcid=0822Nq3FiTMGdIQVF9rKeBvL#rd)



#### 官方文档

[PyTorch](https://pytorch-cn.readthedocs.io/zh/latest/)

[TensorFlow 2官方中文文档](https://www.tensorflow.org/guide?hl=zh-cn)

[scikit-learn](https://scikit-learn.org/stable/) | [中文文档](https://www.scikitlearn.com.cn/) | [Scikit-learn学习](https://zhuanlan.zhihu.com/p/38160930)

[openpyxl - A Python library to read/write Excel 2010 xlsx/xlsm files](https://openpyxl.readthedocs.io/en/stable/)



#### 其他

[Github开源人脸识别项目face_recognition](https://www.cnblogs.com/vactor/p/11832577.html) | [Modern Face Recognition with Deep Learning](https://www.researchgate.net/publication/327938212_Modern_Face_Recognition_with_Deep_Learning)

[如何用Python和深度神经网络寻找近似图片？](https://www.jianshu.com/p/6fe5c75a8aa5)

[如何深度理解RNN？——看图就好！](https://blog.csdn.net/weixin_33939380/article/details/88747922)

[【原】十分钟搞定pandas](https://www.cnblogs.com/chaosimple/p/4153083.html)

[爬取朋友圈，Get年度关键词](https://mp.weixin.qq.com/s/sdJ8_eRLB585TKfg8q72LQ)

[CS224n笔记1 自然语言处理与深度学习简介](http://www.hankcs.com/nlp/cs224n-introduction-to-nlp-and-deep-learning.html#h3-1) | [ImageNet](http://www.image-net.org/)