{"cells":[{"metadata":{},"cell_type":"markdown","source":"<span style=\"font-family:Microsoft YaHei; font-size:1.5em;\">生成狗学习与参与竞赛 Generative Dog Learning and Joining The Contest</span>\n---\n\n> This is a beginner on the kaggle competition platform at first, so this notebook will not provide completed English version. Only if I have wish to get a medal, I will translate it. (*^▽^*)"},{"metadata":{},"cell_type":"markdown","source":"# 胡乱叭叭\n\n[TOC]\n\n```shell\n# 好像并不支持[TOC标签呢……]\n```\n\n```c\n#include <stdio.h>\nint main(){\n    printf(\"hello world!\");\n    return 0;\n}\n```\n\n```python\nprint(\"hello world\");\n```\n\n```shell\n# 好像代码区块支持的也不太好看\n```\n\nkaggle kernel竟然只解析h1标签……好吧……\n\n这里先废话一波吧，我觉得也没人看我这个notebook。这是我第一次参加kaggle competition，所以权当练手了，现在这个阶段名次不重要，重要的是要把这个玩意能做出来， 然后再想着调优吧。\n\n这个kernel刚建起来，下面是生成的使用指南，稍微翻译了下。右侧workspace有个输入文件夹，也是下文所说的文件夹，里面有生成狗的数据，看上去还是很直观的。右下角可以开启GPU和Internet，虽然我不知道Internet这个玩意是干嘛的。另外还能安装包，虽然开启了GPU之后就不能安装了，但最神奇的是支持pip和github两种方式，我觉得开了眼了。\n\n这个操作与jupyter notebook挺像的，所以我觉的这个对我来说还是挺友好的。\n\n弘斐哥说的这个玩意确实是个移动的jupyter，确实没必要在本地配置环境了，但是问题是在于，这玩意第一有的时候会被qiang，第二是GPU资源申请是需要排队的。所以我觉的吧，还是得在本地搭个kaggle docker。这两天搭起来出个总结。\n\n先这样吧。\n\n* 测试下kagglemarkdown怎么样\n* 没别的，很好。\n\n----\n\n1. 再测试下kaggle markdown\n1. 没别的，挺好的\n\n# 正题时间"},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# 这是个python3环境，自带了很多分析库\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# 这是由kaggle/python docker镜像所构建的：https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n# 例如，接下来就是为你导入了有用的一堆包\n\nimport numpy as np # linear algebra 线代\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv) 数据处理，csv测试的输入输出 例如pd.read_csv\n\n# Input data files are available in the \"../input/\" directory.\n# 可以将存放在../input/文件夹内的文件输入为数据文件\n# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n# 例如，运行这个（Shift+Enter）将会列出输入文件夹里有什么东东\n\nimport os\nprint(os.listdir(\"../input\"))\n\n# Any results you write to the current directory are saved as output.\n# 任何结果你写入这个当前文件夹的内容，都会输出在这个结果内","execution_count":null,"outputs":[]},{"metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","collapsed":true,"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","trusted":false},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.4","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}