프로젝트 주피터

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Pythagoras0 (토론 | 기여)님의 2020년 12월 16일 (수) 09:17 판 (→‎노트: 새 문단)
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노트

  • Take a look at my posts on Setting up Anaconda and Jupyter Notebook, and Setting up EC2 for Jupyter Notebook on AWS.[1]
  • If you have an existing Jupyter notebook on your Google Drive, simply click on File/Open drive notebook to open it.[1]
  • Jupyter Notebook was created to make it easier to show one’s programming work, and to let others join in.[2]
  • Jupyter Notebook lets you author visualizations, but also share them and allow interactive changes to the shared code and data set.[2]
  • With a Jupyter Notebook, you can view code, execute it, and display the results directly in your web browser.[2]
  • Because Jupyter Notebook is built on web technology, it can display all the types of multimedia supported in a web page.[2]
  • (This is just an example of what Jupyter Notebook can do, don’t feel like you need to understand it just yet![3]
  • If you can’t get Jupyter Notebook to work on your computer at all, there’s a hosted service called Wakari that you can use for free.[3]
  • You interact with Jupyter Notebook using your web browser.[3]
  • On Linux or OS X, you can start Jupyter Notebook from the command line.[3]
  • If the Jupyter Notebook doesn't open automatically in your browser, copy and paste the URL provided by the command line into your browser.[4]
  • When running in Jupyter Notebook, the Q# code is compiled, and the cell outputs the name of any operations that it finds.[4]
  • The operations that should be completed in order to have Jupyter Notebook ready to use on local server.[5]
  • The bulk of this tutorial discusses executing python code in Jupyter notebooks.[6]
  • You can also use Jupyter notebooks to execute R code.[6]
  • There are many ways to share a static Jupyter notebook with others, such as posting it on GitHub or sharing an nbviewer link.[7]
  • But what if you want to share a fully interactive Jupyter notebook that doesn't require any installation?[7]
  • In this post, I'm going to review six services you can use to easily run your Jupyter notebook in the cloud.[7]
  • Users don't have to create an account, and they'll feel right at home if they already know how to use the Jupyter Notebook.[7]
  • The command starts Jupyter Notebook and opens it in your default web browser as shown below.[8]
  • It also allows Jupyter Notebook to support multiple languages.[9]
  • If you’d rather watch a video instead of read an article, please watch the following instructions on how to use a Jupyter Notebook.[9]
  • To launch a Jupyter notebook, open your terminal and navigate to the directory where you would like to save your notebook.[9]
  • Lastly, in 2014, Project Jupyter started as a spin-off project from IPython.[10]
  • Don't miss this gallery of interesting IPython notebooks or this KDnuggets article.[10]
  • Your Kubeflow deployment includes support for spawning and managing Jupyter notebooks.[11]
  • In this tutorial, you use a locally hosted Jupyter notebook.[12]
  • Note: Semicolons are not normally used in Python, but in Jupyter notebooks, they can be used to suppress the output of the function.[12]
  • The IPython Notebook is now known as the Jupyter Notebook.[13]
  • For more details on the Jupyter Notebook, please see the Jupyter website.[13]
  • Note: By default, the Visual Studio Code Python extension will open a Jupyter Notebook (.ipynb) in the Notebook Editor.[14]
  • It's possible for malicious source code to be contained in a Jupyter Notebook.[14]
  • You can export a Jupyter Notebook as a Python file (.py), a PDF, or an HTML file.[14]
  • Using the add cell icons at the top and bottom of the Jupyter Notebook, will add a code cell at the top and bottom respectively.[14]
  • In 2015, Jupyter notebook was released as a part of The Big Split™ of the IPython codebase.[15]
  • You need some configuration before starting Jupyter notebook remotely.[15]
  • Google’s Colaboratory project, for instance, provides a Google-themed front-end to the Jupyter notebook.[16]
  • One is JupyterHub, a service that allows institutions to provide Jupyter notebooks to large pools of users.[16]
  • The purpose of Jupyter notebooks is to provide a more accessible interface for code used in digitally-supported research or pedagogy.[17]
  • Jupyter Notebook (not to be confused with the Jupyter notebook files themselves, which have an .ipynb extension), and the newer Jupyter Lab.[17]
  • If you are using the command line to launch Jupyter Notebook, pay attention to the directory you are in when you launch it.[17]
  • The Jupyter Notebook file browser interface is the main way to open a Jupyter notebook (.ipynb) file.[17]
  • The Jupyter Notebook is an incredibly powerful tool for interactively developing and presenting data science projects.[18]
  • (In fact, this article was written as a Jupyter Notebook![18]
  • Your first Jupyter Notebook will open in new tab — each notebook uses its own tab because you can open multiple notebooks simultaneously.[18]
  • Provided as a free service as part of Project Jupyter, it is available at nbviewer.jupyter.org.[18]
  • Spun off from IPython in 2014 by Fernando Pérez, Project Jupyter supports execution environments in several dozen languages.[19]
  • Jupyter Notebook (formerly IPython Notebooks) is a web-based interactive computational environment for creating Jupyter notebook documents.[19]
  • Jupyter Notebook can connect to many kernels to allow programming in different languages.[19]
  • To start the Jupyter Notebook, click on Launch, which will take you to the Jupyter homepage.[20]
  • You can rename the Jupyter Notebook by clicking on Untitled.[20]
  • A Jupyter Notebook can be downloaded in multiple formats.[20]
  • Jupyter Notebook is an open source web application that allows you to create interactive Python documents.[21]
  • One way to code in Python is to use a Jupyter notebook.[22]
  • If you are viewing this section as a Jupyter notebook, the text you are now reading is in a text cell.[22]

소스

  1. ↑ 1.0 1.1 Running Jupyter Notebook on Colab
  2. ↑ 2.0 2.1 2.2 2.3 What is Jupyter Notebook? Data analysis made easier
  3. ↑ 3.0 3.1 3.2 3.3 OpenTechSchool – Introducing Jupyter Notebook
  4. ↑ 4.0 4.1 Develop with Q# Jupyter Notebooks - Microsoft Quantum
  5. ↑ Download, Install and Execute Jupyter Notebook Environment
  6. ↑ 6.0 6.1 Jupyter Notebook Tutorial
  7. ↑ 7.0 7.1 7.2 7.3 Six easy ways to run your Jupyter Notebook in the cloud
  8. ↑ Using the Jupyter Notebook environment
  9. ↑ 9.0 9.1 9.2 How To Use Jupyter Notebooks
  10. ↑ 10.0 10.1 (Tutorial) Jupyter Notebook: The Definitive Guide
  11. ↑ Jupyter Notebooks
  12. ↑ 12.0 12.1 Visualizing BigQuery data in a Jupyter notebook
  13. ↑ 13.0 13.1 The Jupyter Notebook — IPython
  14. ↑ 14.0 14.1 14.2 14.3 Working with Jupyter Notebooks in Visual Studio Code
  15. ↑ 15.0 15.1 jupyter/notebook: Jupyter Interactive Notebook
  16. ↑ 16.0 16.1 Why Jupyter is data scientists’ computational notebook of choice
  17. ↑ 17.0 17.1 17.2 17.3 Introduction to Jupyter Notebooks
  18. ↑ 18.0 18.1 18.2 18.3 How to Use Jupyter Notebook in 2020: A Beginner’s Tutorial
  19. ↑ 19.0 19.1 19.2 Project Jupyter
  20. ↑ 20.0 20.1 20.2 Getting Started With Jupyter Network
  21. ↑ Jupyter Notebook
  22. ↑ 22.0 22.1 Python and Jupyter Notebooks
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