Module 4 Summary模块 4 总结

Congratulations! You have completed this module. At this point in the course, you know:
恭喜！您已完成本模块。此时，您在课程中已经知道：

• Jupyter Notebooks are used in Data Science for recording experiments and projects.
  Jupyter Notebook 用于数据科学中记录实验和项目。
• Jupyter Lab is compatible with many files and Data Science languages.
  Jupyter Lab 兼容多种文件和数据科学语言。
• There are different ways to install and use Jupyter Notebooks.
  安装和使用 Jupyter Notebook 有不同方法。
• How to run, delete, and insert a code cell in Jupyter Notebooks.
  如何在 Jupyter Notebook 中运行、删除和插入代码单元。
• How to run multiple notebooks at the same time.
  如何同时运行多个笔记本。
• How to present a notebook using a combination of Markdown and code cells.
  如何使用 Markdown 和代码单元的组合来展示笔记本。
• How to shut down your notebook sessions after you have completed your work on them.
  如何在完成对笔记本的工作后关闭您的笔记本会话。
• Jupyter implements a two-process model with a kernel and a client.
  Jupyter 采用双进程模型，包含一个内核和一个客户端。
• The notebook server is responsible for saving and loading the notebooks.
  笔记本服务器负责保存和加载笔记本。
• The kernel executes the cells of code contained in the Notebook. 
  内核执行笔记本中包含的代码单元。
• The Jupyter architecture uses the NB convert tool to convert files to other formats.
  Jupyter 架构使用 NB 转换工具将文件转换为其他格式。
• The Anaconda Navigator GUI can launch multiple applications on a local device.
  Anaconda Navigator 图形界面可以在本地设备上启动多个应用程序。
• Jupyter environments in the Anaconda Navigator include JupyterLab and VS Code.
  Anaconda Navigator 中的 Jupyter 环境 包括 JupyterLab 和 VS Code。
• You can download Jupyter environments separately from the Anaconda Navigator, but they may not be configured properly.
  您可以从 Anaconda Navigator 中单独下载 Jupyter 环境，但它们可能没有被正确配置。
• Additional open-source Jupyter environments include JupyterLab, JupyterLite, VS Code, and Google Colaboratory. 
  其他开源的 Jupyter 环境包括 JupyterLab、JupyterLite、VS Code 和 Google Colaboratory。
• JupyterLite is a browser-based tool.
  JupyterLite 是一个基于浏览器的工具。