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Python might be the bread-and-butter coding language for data scientists and ML practitioners, but the benefits of becoming a programming polyglot are as clear as ever. The projects that data teams work on cross platforms and architectures, and being able to switch to less common—but sometimes more efficient—languages can be a powerful advantage.
For our highlights this week, we chose recent articles that cover a lot of ground: they focus on a wide range of languages, projects, and workflows. These posts invite you to roll up your proverbial sleeves and start tinkering with some code—and they might just inspire you to expand your knowledge even further.
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