Data-Science

Nteract : An interactive computing environment

A slide deck from Netflix, mentions using Nteract as their programming notebook, and prompted a mini exploration. This blog post by Safia Abdalla, (a maintainer/ developer of Nteract) introduces Nteract as an open source, desktop-based, interactive computing application that was designed to overcome a bunch of limitations in Jupyter Notebook’s design philosophy. One key difference (among many others) is the ability to execute code in a variety of languages within a single notebook, and it also appears that that the electron based desktop app should make it easier for beginners to start coding.

Rapidly accessing cheatsheets to learn data science with Emacs

Matt Dancho’s course DSB-101-R is an awesome course to step into ROI driven business analytics fueled by Data Science. In this course, among many other things - he teaches methods to understand and use cheatsheets to gain rapid level-ups, especially to find information connecting various packages and functions and workflows. I have been hooked to this approach and needed a way to quickly refer to the different cheatsheets as needed.

Technical notes : Research paper on learning/teaching data science

Title: Navigating Diverse Data Science Learning: Critical Reflections Towards Future Practice Author: Yehia Elkhatib Download link This are my notes on the above paper, which mainly deals with detailing the methods explored and implemented to impart a high quality of education in data science. The paper also provides an interesting breakup of the different roles in data science workflows. The importance of being able to work in a team is highlighted.