How to Create Jupyter Notebook Locally

Learn how to create a Jupyter Notebook locally on your machine.

We'll cover the following

Hardware requirements

For the optimal student experience, we recommend the following hardware configuration:

  • Processor: Intel Core i5 or equivalent

  • Memory: 4 GB RAM

  • Storage: 35 GB available space

Software requirements

You'll also need the following software installed in advance:

  • OS: Windows 7 SP1 64-bit, Windows 8.1 64-bit or Windows 10 64-bit, Ubuntu Linux, or the latest version of OS X

  • Browser: Google Chrome/Mozilla Firefox Latest Version

  • Notepad++/Sublime Text as IDE (this is optional, as you can practice everything using the Jupyter Notebook on your browser)

  • Python 3.8+ (This course uses Python 3.8.2) installed (from the Python website, or via Anaconda as recommended below) . At the time of writing, the SHAP library used in chapter "Gradient Boosting, XGBoost, and SHAP Values", is not compatible with Python 3.9. Therefore, if you are using Python 3.9 as your base environment, we suggest that you set up a Python 3.8 environment as described in the next section.

  • Python libraries as needed (Jupyter, NumPy, Pandas, Matplotlib, and so on, installed via Anaconda as recommended below)

Installation and setup

If you plan on running the codes locally, it is recommended to install the Anaconda package manager and use it to coordinate the installation of Python and its packages.

Anaconda and setting up your environment

You can install Anaconda by visiting the Anaconda website. Scroll down to the bottom of the page and download the installer relevant to your system.

It is recommended to create an environment in Anaconda to do the exercises and activities in this course, which have been tested against the software versions indicated here. Once you have Anaconda installed, open a Terminal, if you're using macOS or Linux, or a Command Prompt window in Windows, and do the following:

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