# All-about-Machine-Learning

**Repository Path**: coracoding/All-about-Machine-Learning

## Basic Information

- **Project Name**: All-about-Machine-Learning
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-03-26
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# 搜索排序入门
- [阿里提出电商搜索全局排序方法，淘宝无线主搜 GMV 提升 5%](https://www.infoq.cn/article/ecommerce-search-ranking)
- [电商搜索算法技术的演进](https://102.alibaba.com/detail?id=189)

# All-about-Machine-Learning
All materials related to Machine Learning is collected here like conferences,books,algorithms and so on.
机器学习的相关资料，包括国际会议、书、算法等等。

## Paper
- [word2vector 论文](https://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf)
- [LSTM论文](https://arxiv.org/pdf/1601.06733.pdf) ；[LSTM ppt](http://people.idsia.ch/~juergen/lstm2003tutorial.pdf) ；[另一篇介绍LSTM的PPT](http://axon.cs.byu.edu/~martinez/classes/778/Papers/lstm.pdf)
- [图神经网络](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.1015.7227&rep=rep1&type=pdf)
- [FM](https://www.csie.ntu.edu.tw/~b97053/paper/Rendle2010FM.pdf);   [FFM](https://www.csie.ntu.edu.tw/~cjlin/papers/ffm.pdf)
- [Wide and Deep](https://arxiv.org/pdf/1606.07792.pdf)
- [BERT](https://arxiv.org/pdf/1810.04805.pdf) 谷歌出的打破各种nlp记录的文章
- [Attation is all you need](https://arxiv.org/pdf/1706.03762.pdf)


## Top Conferences   
- SIGMOD (Special Interest Group on Management Of Data). Focus on data analytics (DanaC), databases and the Web (WebDB), exploratory search (ExploreDB), managing and mining spatial data (GeoRich), and graph data (GRADES) in 2015.
- KDD (Knowledge Discovery and Data Mining). 
- CVPR
- NIPS
- SIGIR


## Websites   
- <http://arxiv.org/> could follow the latest papers.   
 
## Books   
- 统计学习方法（李航）    
- 机器学习（周志华）
- 数学之美（吴军）  

## 框架
- [Tutorial to Tensorflow](https://www.oreilly.com/learning/hello-tensorflow)   
- [XGBoost 0.8官方手册](https://media.readthedocs.org/pdf/xgboost/latest/xgboost.pdf)


## MapReduce   
- [How to Write a MapReduce Program](https://www.mapr.com/blog/how-write-mapreduce-program)    

## 工具
- [Latex初学指南](http://www.docs.is.ed.ac.uk/skills/documents/3722/3722-2014.pdf)