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   "source": [
    "# 1.5 实践方式\n",
    "课程中的课后作业大都可以通过两种方式完成，一种是通过Kaggle平台，一种是通过自建环境完成。\n",
    "比较建议通过Kaggle平台完成，因为课程所有的代码，数据集都已经部署在了此平台上，且此平台提供免费的算力，仅仅只需要浏览器就可完成所有的课程作业，比较适合初学者\n",
    "而自建环境则意味着，你需要自己构建代码的运行环境，下载对应的数据集，完成相应的作业，适合希望进一步学习Python的同学"
   ]
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   "source": [
    "## 实践方式一: Kaggle（建议采用）\n",
    "课程所有的数据，代码都部署到了 kaggle 平台上。使用此方式参与到课程学习中无需下载数据，配置Python运行环境。所有的代码均可通过网页浏览学习，编辑运行。但此方式需要注册Kaggle账号，注册过程比较麻烦，Kaggle使用过程中有任何疑问可与课程助教联系。\n",
    "以此种方式完成实践需要完成以下五个步骤："
   ]
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   "source": [
    "### 1.注册Kaggle账号\n",
    "进入Kaggle平台，链接如下，点击按钮Register\n",
    "\n",
    "https://www.kaggle.com/account/login?phase=startRegisterTab"
   ]
  },
  {
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   "source": [
    "![1](images/kaggle1.png)"
   ]
  },
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   "metadata": {},
   "source": [
    "选择使用邮箱注册或者采用谷歌账号注册。采用邮箱注册时，会遇到一个问题无法接收到Google的人机验证小程序，即Captcha must be filled out。"
   ]
  },
  {
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   "metadata": {},
   "source": [
    "![2](images/kaggle2.png)"
   ]
  },
  {
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   "metadata": {},
   "source": [
    "这里需要借用一下下列的知乎教程，将Google的人机验证小程序重定向到可以访问的网站，使得我们可以通过验证。\n",
    "\n",
    "https://zhuanlan.zhihu.com/p/607977683\n",
    "\n",
    "此教程中需要的文件（Header Editor.crx）和重定向规则（HE-GoogleRedirect.json）都已放到师大云盘中, 如果你的浏览器是Edge，请在浏览器的拓展程序商店中搜索Header Editor\n",
    "\n",
    "https://www.azurezeng.com/static/HE-GoogleRedirect.json\n",
    "\n",
    "https://pan.bnu.edu.cn/l/XFUh1k\n",
    "\n",
    "如果你的浏览器是Chrome，不允许添加离线的拓展程序，请参考下面的简书文档。\n",
    "\n",
    "https://www.jianshu.com/p/a1248c522899\n",
    "\n",
    "完成上述重定向后，Google的人机验证小程序即可出现，可继续通过邮箱注册。"
   ]
  },
  {
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   "metadata": {},
   "source": [
    "![3](images/kaggle3.png)"
   ]
  },
  {
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   "metadata": {},
   "source": [
    "### 2.加入课程实践"
   ]
  },
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   "metadata": {},
   "source": [
    "回到课程Kaggle的主界面，在登陆的状态下点击右上角黑色按钮**Join Competition**,以homework3中土地覆盖分类为例\n",
    "\n",
    "https://www.kaggle.com/competitions/prors-hw"
   ]
  },
  {
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   "metadata": {},
   "source": [
    "![4](images/kaggle4.png)"
   ]
  },
  {
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   "metadata": {},
   "source": [
    "先后浏览Overview，Data，Code了解实践相关内容，选学部分可不看。"
   ]
  },
  {
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   "metadata": {},
   "source": [
    "### 3.创建自己的Notebook"
   ]
  },
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   "metadata": {},
   "source": [
    "课程的代码模版如下面的链接所示，同样也可以通过课程主界面的**Code**栏目进入，大家可以直接点击网页右上角的**Copy & Edit**进行复制并编辑。\n",
    "https://www.kaggle.com/code/haozeshi/prors-luc-cla"
   ]
  },
  {
   "attachments": {},
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   "metadata": {},
   "source": [
    "![5](images/kaggle5.png)"
   ]
  },
  {
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   "metadata": {},
   "source": [
    "进入后可直接在网页中基于课程提供的代码模版编辑，调试，运行代码，输出结果。"
   ]
  },
  {
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   "metadata": {},
   "source": [
    "![6](images/kaggle6.png)"
   ]
  },
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   "source": [
    "### 4.保存Notebook与输出结果\n",
    "运行完成后，点击右上角的黑色按钮**Save Version**保存Notebook，建议采用**Quick save**，一定勾选保存**Always save output when creating a Quick Save**。"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![7](images/kaggle7.png)"
   ]
  },
  {
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   "source": [
    "### 5.提交结果与评分\n",
    "回到Notebook，来到**Notebook**的**Data**界面，选中**submission.csv**提交自己的预测结果便可获取自己的预测得分。"
   ]
  },
  {
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   "source": [
    "![8](images/kaggle8.png)\n",
    "![9](images/kaggle9.png)\n",
    "![10](images/kaggle10.png)"
   ]
  },
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   "source": [
    "## 实践方式二：自建环境"
   ]
  },
  {
   "attachments": {},
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   "metadata": {},
   "source": [
    "适合已经配置好环境，或者想要学习Python语言的同学。课程所有的数据，代码都已经上传到师大云盘 ，需要大家自己下载运行，师大云盘其内容同kaggle一致。有任何配置上的问题可与本课程的助教联系。\n",
    "\n",
    "师大云盘链接如下：\n",
    "\n",
    "https://pan.bnu.edu.cn/l/XFUh1k\n",
    "\n",
    "实践方式2和实践方式1的主要差别在与第3步、第4步，即Notebook将在你本地电脑上运行，最终预测的结果仍需提交到Kaggle之中，所以还是建议采用方式一进行实践。\n",
    "\n",
    "关于Python环境的配置与搭建，大家可以参考此文档\n",
    "\n",
    "https://www.jianshu.com/p/ef1ae10ba950\n",
    "\n",
    "安装好Anaconda后启动Notebook即可，\n",
    "\n",
    "最终预测的结果需提交到Kaggle之中，注册提交方式可参考实践方式一中第1，2，5步\n",
    "\n",
    "即进入Kaggle\n",
    "\n",
    "https://www.kaggle.com/competitions/prors-hw\n",
    "\n"
   ]
  },
  {
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "点击右上角 Sign in，根据提示完成 Kaggle 注册。然后点击 Join Competition然后点击 Submit Predictions 。"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![11](images/kaggle11.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
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   "outputs": [],
   "source": [
    "上传预测结果，并得到评分 。\t注意预测结果的格式需与提供的模版一致。\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![12](images/kaggle12.png)"
   ]
  }
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