Setting VSCode as the default editor was pretty straight forward. So far, I was only using it when willing to add the description of my commits in Git. VSCode can be a good tool for machine learning and data science if you need a code editor with an integrated terminal, robust debugging, support for extensions, a user-friendly interface, and customization options.For different reasons, I recently decided to start using VSCode more generally. You can also customize keyboard shortcuts, themes, and other settings to improve your workflow. Customization: VSCode is highly customizable, allowing you to customize the look and feel of the code editor to meet your needs.This makes it a suitable choice for beginners and experienced developers alike.

User-friendly interface: VSCode has a user-friendly interface that makes it easy to navigate, edit, and organize code.These extensions can enhance the functionality of VSCode and make it easier to work with data and machine learning models. Extensions: VSCode has a large library of extensions, including those specifically designed for data science and machine learning, such as Jupyter, Pandas, and Matplotlib.Debugging: VSCode has robust debugging capabilities, including support for Python debugging, which is crucial for finding and fixing errors in machine learning and data science code.This is useful for running data science and machine learning scripts. Integrated Terminal: VSCode has an integrated terminal that allows you to run shell commands and interact with your operating system directly from the code editor.It has many features that make it a suitable choice for these tasks, including: Visual Studio Code (VSCode) is a good tool for machine learning and data science.

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