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Jupyter Notebooks vs Google Colab

 


  1. Jupyter Notebooks:

    • What It Is: Jupyter Notebooks is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text.
    • Local Setup: It runs on your own computer. You need to install Python and any libraries you want to use.
    • Usage: It’s great for experimenting with code and data analysis in Python.

  2. Google Colab:

    • What It Is: Google Colab, or “Colaboratory”, is a free service from Google Research.
    • Cloud-Based: It operates on Google’s cloud servers, which means you can access it from anywhere with an internet connection.
    • No Setup Needed: It comes with most of the Python libraries you’ll need pre-installed.
    • GPU Support: It provides free access to GPUs (Graphics Processing Units) which can speed up certain types of computations.
    • Collaboration: You can easily share your Colab notebooks and collaborate with others in real time.
    • Integration with Google Drive: It integrates with Google Drive, making it easy to save your work and access files.

For a Novice to Python:

  • Python: It’s a programming language that’s known for its readability and versatility.
  • Libraries: These are collections of pre-written code that you can use to add functionality to your Python programs without having to write the code yourself.

Starting with Jupyter Notebooks:

  1. Install Python: Download and install Python from the official website.
  2. Install Jupyter: Use pip, Python’s package manager, to install Jupyter by running pip install jupyter in your command line.
  3. Launch Jupyter: Run jupyter notebook in your command line to start Jupyter and use it in your web browser.

Starting with Google Colab:

  1. Google Account: Make sure you have a Google account.
  2. Access Colab: Go to the Google Colab website and log in with your Google account.
  3. Create a New Notebook: Click on ‘New Notebook’ to start coding in Python right away.

Both environments are excellent for learning and doing data science with Python. They allow you to write and run Python code, see the results, and explain what you did in a document-like format.

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