This week I started studying Natural Language Processing and Computational Linguistics with Python. As many, I use Conda for managing my Python environments and packages. On this post I will cover how to create new environments on Conda and how to use them with JupyterLab.
JupyterLab has quickly become the standard for doing Data Science in Python. Arguably, the main reason for this is the notebook format, an idea introduced back in 1986 in the amazing Wolfram Mathematica.
But the fact is there are just no decent alternatives.
So today I was making quite time consuming simulations in R, and I was wondering if there was a way to know when the simulations were finished so I could have a look at the results.