data, it's a kind of magic

Over the past years I’ve always been a Sublime Text guy. I’ve also been a C# guy on Visual Studio so, naturally, when I heard about Visual Studio Code (VSC) I would give it a try. Three months later, I’ve never looked back. The built-in git diff viewer, Markdown previewer, debugger, linting, and IntelliSense (code autocomplete)? Thumbs up. Sure, you could add packages to do most of those in Sublime, but those solutions aren’t nearly as elegant as VSC. Not to mention, Sublime’s UI just somehow feels… I don’t know… dated?

If you are balking at learning yet another editor, just do it. Naturally there will be the initial familiarization hurdle to overcome, but once you get started I’m sure you too will quickly leave Sublime in the dust. Here are some tips and tricks I’ve aggregated so far.

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macOS and Linux, the de facto OSes of choice due to their ease of use and compatibility with tooling, right? Then what’s this I’m hearing lately? The winds of change whispering after the ho-hum new Macbook Pro?

With Windows 10’s new Windows Subsystem for Linux (WSL) aka Bash on Ubuntu on Windows on the fast track to becoming a full fledged Linux VM replacement, there is little, if anything, in our data science stack that can’t run on a Windows box. It might actually, knock on wood, become preferrable to do so soon. Take a look at TensorFlow’s performance on Windows. If you have a Nvidia 10-series GPU, you’ll be wiping the floor with Macs.

Hold up for a moment though. Since WSL is still in beta, there are a handful of gotchas that you’ll need to address. This guide aims to outline all the steps necessary to get you up and data crunching. If you find it too verbose, just do the Quick Start section.

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