Alan Zhao

Aug 28, 2017

Resources and Inspiration Online

As much of my learning has come from online resources as from Swarthmore or Yale classrooms. This is my attempt to share some of the absolute best blogs I've encountered. They run the gamut from very technical to purely practical. I'll periodically add to this as I find more.

Practical Business Python

http://pbpython.com/

The blog that started it all. Written by Chris Moffitt, an engineer by training but finance guy by trade, this blog is focused on showcasing how Python can take on business analysis usually left to Excel. Example topics include using pandas for pivot tables, and streamlining bulk generation of Excel reports. This blog inspired me to learn Python more deeply and provided numerous insights to automate work; at my old nonprofit we even used some posts as training material. Most importantly of all, a conversation with Chris himself led me to the idea of creating this blog.

Math union Programming

https://jeremykun.com/

Written by Jeremy Kun, a math PhD turned software engineer, this blog covers a variety of mathematical topics (ie optimization, statistics, etc). What's interesting is that it is all done from a coder's perspective, focusing on intuition and programmatic examples rather than endless equations. His article on support vector machines is illustrative of this. Many of his posts has helped clarify several concepts from graduate level statistics courses I took at Yale.

Own your bits

https://ownyourbits.com/

Written by a hacker "Narcho," this blog focuses on leveraging the raspberry pi as a home cloud storage solution. In other words, a DIY dropbox. A great DIY project that I did over the past winter break with a leftover portable hard drive.

Narcho himself is an ardent advocate of understanding all technology used in daily life, particularly the hardware side. Obviously impractical to do for everything, but an admirable mindset to drive your curiosity.

John Myles White's Blog

http://www.johnmyleswhite.com/

Another blog attempting to explain statistical content in a colloquially understandable, but mathematically rigorous way. His optimization perspective on mean, median, and mode was eye-opening for me.