Overcoming 5 Hurdles to Using Jupyter Notebooks for Data Science, by the JetBrains Datalore Team

Jupyter has a really great community and is one of the most successful open-source projects ever. However, classic Jupyter, or Jupyter notebooks, as well as many solutions built upon it, aren’t free of inherent problems. Today we’ll talk about the major ones and how our team has tackled them in Datalore – a data science notebook platform for teams that’s available both in cloud and enterprise setups.

This session took place in track Jupyter and was classified suitable for some domain / some python by the speaker.

Alena Guzharina

About — in the speaker's own words

I do my best to communicate the cool things we do for data science teams at Datalore. I graduated as a data scientist, and am passionate about marketing and tech.

Product Marketing Manager for JetBrains Datalore

Social card for talk: Overcoming 5 Hurdles to Using Jupyter Notebooks for Data Science, by the JetBrains Datalore Team