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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 1. 项目介绍\n",
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"\n",
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" - 项目是由模块组成、有特定功能的程序。它能够满足用户的直接使用需求，例如[古诗词生成器](https://momodel.cn/explore/5bfb634e1afd943c623dd9cf?type=app&tab=1)、[风格迁移](https://momodel.cn/explore/5bfb634e1afd943c623dd9cf?type=app&tab=1)等。\n",
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" - 开发项目过程中你可以导入数据集，也可以通过每个 cell 上方工具栏的`<+>`直接插入[模块](https://momodel.cn/modules)和代码块。\n",
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" - 你可以将开发好的项目进行[部署](https://momodel.cn/docs/#/zh-cn/%E5%BC%80%E5%8F%91%E5%92%8C%E9%83%A8%E7%BD%B2%E4%B8%80%E4%B8%AA%E9%A1%B9%E7%9B%AE)，项目部署成功并选择正式版本发布后会展示在“项目”页面，用户可以在线使用，也可以通过 API 调用。\n",
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"\n",
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" - 项目目录结构:\n",
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"\n",
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" - ```results```*-----结果的文件存放地(如果你运行 job，务必将运行结果指定在此目录)*\n",
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" - ```_OVERVIEW.md``` *-----项目的相关介绍*\n",
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" - ```_README.md```*-----说明文档*\n",
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" - ```app_spec.yml```*-----定义项目的输入输出，为部署服务*\n",
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" - ```coding_here.ipynb```*-----输入并运行代码*"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n",
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"## 2. 开发环境简介\n",
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"\n",
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"你当前所在的页面 Notebook 是一个内嵌 JupyterLab 的在线类 IDE 编程环境，开发过程中可以使用页面右侧的 API 文档进行快速查询。Notebook 有以下主要功能：\n",
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"\n",
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"- [调用数据集、模块和代码块资源](https://momodel.cn/docs/#/zh-cn/%E5%A6%82%E4%BD%95%E5%AF%BC%E5%85%A5%E5%B9%B6%E4%BD%BF%E7%94%A8%E6%A8%A1%E5%9D%97%E5%92%8C%E6%95%B0%E6%8D%AE%E9%9B%86)\n",
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"- [多人代码协作](https://momodel.cn/docs/#/zh-cn/%E5%9C%A8Mo%E8%BF%90%E8%A1%8C%E4%BD%A0%E7%9A%84%E7%AC%AC%E4%B8%80%E6%AE%B5%E4%BB%A3%E7%A0%81?id=_7-%e4%bd%a0%e5%8f%af%e4%bb%a5%e9%82%80%e8%af%b7%e5%a5%bd%e5%8f%8b%e8%bf%9b%e8%a1%8c%e5%8d%8f%e4%bd%9c)\n",
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"- [在 GPU 资源上训练机器学习模型](https://momodel.cn/docs/#/zh-cn/%E5%9C%A8GPU%E6%88%96CPU%E8%B5%84%E6%BA%90%E4%B8%8A%E8%AE%AD%E7%BB%83%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E6%A8%A1%E5%9E%8B)\n",
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"- [简单部署](https://momodel.cn/docs/#/zh-cn/%E5%BC%80%E5%8F%91%E5%92%8C%E9%83%A8%E7%BD%B2%E4%B8%80%E4%B8%AA%E9%A1%B9%E7%9B%AE)\n",
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"\n",
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"快来动手试试吧！点击左侧工具栏的新建文件图标即可选择你需要的文件类型。\n",
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"\n",
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"<img src='https://imgbed.momodel.cn/006tNc79gy1g61agfcv23j31c30u0789.jpg' width=100% height=100%>\n",
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"\n",
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"\n",
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"\n",
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"左侧和右侧工具栏都可根据使用需要进行收合。\n",
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"<img src='https://imgbed.momodel.cn/collapse_tab.2019-09-06 11_07_44.gif' width=100% height=100%>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 3. 快捷键与代码补全\n",
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"Mo Notebook 已完全采用 Jupyter Notebook 的原生快捷键，并且支持 `tab` 代码补全。\n",
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"\n",
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"运行代码：`shift` + `enter` 或者 `shift` + `return`"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 4. 常用指令介绍\n",
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"\n",
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"- 解压上传后的文件\n",
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"\n",
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"在 cell 中输入并运行以下命令：\n",
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"```!7zx file_name.zip```\n",
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"\n",
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"- 查看所有包（package）\n",
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"\n",
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"`!pip list --format=columns`\n",
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"\n",
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"- 检查是否已有某个包\n",
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"\n",
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"`!pip show package_name`\n",
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"\n",
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"- 安装缺失的包\n",
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"\n",
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"`!pip install package_name`\n",
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"\n",
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"- 更新已有的包\n",
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"\n",
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"`!pip install package_name --upgrade`\n",
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"\n",
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"\n",
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"- 使用包\n",
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"\n",
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"`import package_name`\n",
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"\n",
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"- 显示当前目录下的档案及目录\n",
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"\n",
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"`ls`\n",
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"\n",
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"- 使用引入的数据集\n",
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"\n",
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"数据集被引入后存放在 datasets 文件夹下，注意，这个文件夹是只读的，不可修改。如果需要修改，可在 Notebook 中使用\n",
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"\n",
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"`!cp -R ./datasets/<imported_dataset_dir> ./<your_folder>`\n",
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"\n",
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"指令将其复制到其他文件夹后再编辑，对于引入的数据集中的 zip 文件，可使用\n",
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"\n",
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"`!7zx ./datasets/<imported_dataset_dir>/<XXX.zip> ./<your_folder>`\n",
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"\n",
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"指令解压缩到其他文件夹后使用"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 5. 其他可参考资源\n",
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"\n",
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"- [帮助文档](https://momodel.cn/docs/#/)：基本页面介绍和常见问题都可以在里面找到\n",
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"- [平台功能教程](https://momodel.cn/classroom/class/5c5696cd1afd9458d456bf54)：通过图文结合的 Notebook 详细介绍开发环境基本功能和操作\n",
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"- [从 Python 到人工智能](https://momodel.cn/classroom/course/detail?&id=60f02c635076ff487bce4c6f)：超易入门的 Python 课程\n",
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"- [吴恩达机器学习](https://momodel.cn/classroom/class/5c5696191afd94720cc94533)：机器学习经典课程\n",
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"- [李宏毅机器学习](https://momodel.cn/classroom/class/5d63dde21afd9461419f5ebf)：中文世界最好的机器学习课程\n",
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"- [机器学习实战](https://momodel.cn/classroom/class/60af61b6f955c61c2cddfcb5)：通过实操指引完成独立的模型，掌握相应的机器学习知识\n",
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"- [深度学习实战](https://momodel.cn/classroom/class/5c680b311afd943a9f70901b)：通过实操指引完成独立的模型，掌握相应的深度学习知识\n",
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"- [模块开发](https://momodel.cn/modules)：关于模型训练、开发与部署的高阶教程"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.5.2"
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},
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"pycharm": {
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"stem_cell": {
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"cell_type": "raw",
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"source": [],
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"metadata": {
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"collapsed": false
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}
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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