Data wrangling (getting, cleansing and transforming data) isn’t always the fun part of Data Science, but it’s a major part of working with data in the real world

Before we jump in with that awesome new algorithm we just learned, we need to make sure we have our data, we’ve modified or removed any problematic entries, and we’ve transformed that data into a form we can work with.
What better way to go about this than with a handy…

So you’re using git for your projects, you’ve got that whole committing thing down, you’re pushing and pulling like a sailor and branching like there’s no tomorrow.

Maybe you feel like you’ve got the basics down but you could do more? …

Daphna Regev

Data Scientist @ Trax. I like clean code, machine learning and sushi, not necessarily in that order.

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