Technical requirements

All of the implementation in this chapter (and the book too) is using the Python programming language. Most standard computers will allow you to run all of the code without any memory or runtime issues.

There are two options for you to run the code in this book, as follows:

• Jupyter Notebook: An interactive code and text notebook with a GUI that will allow you to run code locally. Real Python has a very good introductory tutorial on getting started at Jupyter Notebook: An Introduction (https://realpython.com/jupyter-notebook-introduction/).
• Google Colab: This is simply the online version of Jupyter Notebook. You can use the free tier as this is sufficient. Be sure to download any data or files that you create, as they disappear after the runtime is cleaned up.

You will need to install a few libraries that we need for our experiments and analysis. A list of libraries is provided as a text file, and all the libraries can be installed using the pip utility with the following command:

pip install –r requirements.txt

In case you get an error for a particular library not found or installed, you can simply install it with pip install <library_name>.

You can find the code files for this chapter on GitHub at https://github.com/PacktPublishing/10-Machine-Learning-Blueprints-You-Should-Know-for-Cybersecurity/tree/main/Chapter%202.