Data Science Papers for Spring 2020

Pain Points, Needs, and Design Opportunities This paper is a study done on the usage of notebooks for data science. It cover a bunch of the negative impacts of using notebooks for data science. Deployment, setup, collaboration, and reliablity are a few of the examples. Quantifying the Carbon Emissions of Machine Learning Training a neural network can take a lot of computer processing power. This processing power comes at a cost to the environment.