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How to Make Your Data Science/ML Engineer Workflow More Effective | by Eivind Kjosbakken | Sep, 2024
Learn how you can use VS Code interactive window to program more effectively
Anyone working with programming needs an effective workflow. Many tasks are time-consuming, and you want to automate as much as possible to reduce manual work. In this article, I discuss how I have recently updated my workflow as a data scientist, moving away from Jupyter Notebooks and to using VS Code interactive windows.
This article discusses how you can effectivize your data science / ML engineering workflow with VS Code interactive windows. Image by ChatGPT.
To showcase the new workflow, I will use some simple code highlighting how you can work faster using the new workflow. You should note, however, that I think the benefits of the new workflow increase the more complex a project becomes. Many problems with Jupyter Notebooks arise when a project grows bigger, and it’s more difficult to have an overview of your data. Thus, I think the benefits of the workflow I am showcasing in this article will only increase with real-world projects. I will use pictures and videos throughout the article to visually showcase how you can work with the VS Code interactive window. My inspiration for this article was this YouTube video from Dave Ebbelaar about how he stopped using Jupyter Notebook.
Images are for reference only.Images and contents gathered automatic from google or 3rd party sources.All rights on the images and contents are with their legal original owners.
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