Jupyter Notebook Best Practices for Data Science

September 15th, 2016 Editor’s note: Welcome to Throwback Thursdays! Every third Thursday of the month, we feature a classic post from the earlier days of our company, gently updated as appropriate. We still find them helpful, and we think you will, too! The original version of this post can be found here. The Jupyter Notebook is a fantastic tool that can be used in many different ways. Because of its flexibility, working with the Notebook on data science problems in a team setting can be challenging. We present here some best-practices that SVDS has implemented after working with the Notebook in teams and with our clients—and that might help your data science teams as well. The need to keep work under version control, and to maintain shared space without getting…


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