# 教程资料 整理一下所收集的教程以及各种资源 --- ## 教程 *标注\*的为视频教程* ### 电子书 - [Github电子书合集](https://github.com/EbookFoundation/free-programming-books/blob/master/free-programming-books-zh.md) - [deep learning 中文版](files/dlbook_cn_public.pdf) - [PRML 中文版](files/PRML.pdf) ### 数学 - [Statistical Analysis Handbook 2018 edition](http://www.statsref.com/HTML/index.html?car_models.html) ### 机器学习相关 - [pytorch](https://pytorch.org/tutorials/) - [tensorflow](https://www.tensorflow.org/overview/) - *[网易云慕课](https://mooc.study.163.com/smartSpec/detail/1001319001.htm)，深度学习微专业，可以由此入门 - *[哔哩哔哩](https://www.bilibili.com/video/av33485817)，我也没学过，看目录很不错 - *[哔哩哔哩](https://space.bilibili.com/97068901/)，一位up主，正在看 - [PyMC3](https://docs.pymc.io/) - [scikit learn](https://scikit-learn.org/stable/documentation.html) ### 深度学习资料 #### 语义分割 - [mrgloom/awesome-semantic-segmentation: awesome-semantic-segmentation (github.com)](https://github.com/mrgloom/awesome-semantic-segmentation) ### 编程开发 - [Python，廖雪峰](https://www.liaoxuefeng.com/wiki/1016959663602400) - [Git，廖雪峰](https://www.liaoxuefeng.com/wiki/896043488029600) - [R语言](https://www.tutorialspoint.com/r/r_basic_syntax.htm) - [Qt学习之路](https://www.devbean.net/2012/08/qt-study-road-2-catelog/) - [Linux尝鲜](https://www.shiyanlou.com/courses/1),实验楼的在线实验，不错的 - [Flask](https://dormousehole.readthedocs.io/en/latest/) - [HTML，菜鸟教程](https://www.runoob.com/html/html-tutorial.html) - [CSS，菜鸟教程](https://www.runoob.com/css/css-tutorial.html) - [JavaScript，菜鸟教程](https://www.runoob.com/js/js-tutorial.html) - [WebGL](https://webglfundamentals.org/webgl/lessons/zh_cn/webgl-fundamentals.html#toc) - [Vue](https://cn.vuejs.org/v2/guide/index.html), [Vue-cli](https://cli.vuejs.org/zh/guide) #### 各类小教程 - [Linux SSH 秘钥远程连接](https://blog.csdn.net/Yvettre/article/details/79493773) - [Django Nginx自动化部署](https://www.zmrenwu.com/courses/hellodjango-blog-tutorial/materials/74/) ### UI库 - [Ant Design](https://vue.ant.design/docs/vue/introduce/) - [Element](https://element.eleme.cn/#/zh-CN) - [阿里巴巴图标库](https://www.iconfont.cn/) ### GIS，RS等 - [Echarts](https://www.echartsjs.com/zh/tutorial.html#5%20%E5%88%86%E9%92%9F%E4%B8%8A%E6%89%8B%20ECharts) - [Cesium](https://cesiumjs.org/Cesium/Build/Documentation/) - [Cesium学习笔记](http://blog.sina.com.cn/s/blog_15e866bbe0102xu2f.html) - [Leaflet for R](http://rstudio.github.io/leaflet/choropleths.html) - [Folium](https://python-visualization.github.io/folium/)，`Leaflet`的 `python`版本 ### VPN - [V2Ray服务端](https://github.com/233boy/v2ray/wiki/V2Ray%E4%B8%80%E9%94%AE%E5%AE%89%E8%A3%85%E8%84%9A%E6%9C%AC) - [Digital Ocean](https://m.do.co/c/74311e35da0c)，也就是你要的服务器 - [V2RayN客户端](https://github.com/233boy/v2ray/wiki/V2RayN%E4%BD%BF%E7%94%A8%E6%95%99%E7%A8%8B)，装在自己电脑上的 ## 资源 - [Kaggle](https://www.kaggle.com/) - [阿里云](https://account.aliyun.com) - [阿里云代码托管](https://code.aliyun.com/) - [腾讯云](https://cloud.tencent.com/) - [Github](https://github.com/) - [GIS空间站](http://www.gissky.net/Category_25/Index.aspx)，貌似挺好的 - [Anaconda清华镜像](https://mirrors.tuna.tsinghua.edu.cn/anaconda/) - [短链接](https://urlgo.run/dashboard/links?userId=20) ### 期刊 - [Remote Sensing of Environment](https://www.journals.elsevier.com/remote-sensing-of-environment) - [IEEE Transactions on Geoscience and Remote Sensing](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=36) - [IEEE Geoscience and Remote Sensing Letters](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8859) - [ISPRS Journal of Photogrammetry and Remote Sensing](https://www.journals.elsevier.com/isprs-journal-of-photogrammetry-and-remote-sensing) - [武大图书馆](http://www.lib.whu.edu.cn/web/default.asp) - [Arxiv](https://arxiv.org/) ### 论文 额，有一些，以后再加 ### 数据资源 - [NASA官网](https://eospso.nasa.gov/) - [遥感数据集，机器学习用](https://zhangbin0917.github.io/2018/06/12/%E9%81%A5%E6%84%9F%E6%95%B0%E6%8D%AE%E9%9B%86/?tdsourcetag=s_pctim_aiomsg)，感谢整理！ - [地理空间数据云](http://www.gscloud.cn/)，有很多免费的影像 - [国家统计局](http://www.stats.gov.cn/) - [EarthExplorer](https://earthexplorer.usgs.gov/)，Landsat等等，这有个[教程](https://malagis.com/andsat-data-download.html) - [JAXA葵花八号数据](https://www.eorc.jaxa.jp/ptree/index.html)需要注册 - [Google Earth Engine](https://developers.google.com/earth-engine/datasets)，好像要翻墙 - [UC Irvine Machine Learning Repository](https://archive.ics.uci.edu/ml/index.php) - [ImageNet](http://www.image-net.org/)，很全，随意下载 - [CoCo](http://cocodataset.org/#home) - [MSDN](https://msdn.itellyou.cn/)