Journey into Data Science & Architecture
A Jack-of-all-Trades and master of none is how I feel professionally.
I’ve always been interested in the science and math side of things and also the creative and aesthetic side. It’s what caused me to switch out of chemical engineering in undergrad to pursue architecture.
And it’s that same motivation driving my journey into data science.
One clear cross-over is the use of diagrams and graphically conveying information. In architecture it’s through diagrams and obviously the actual drawing set that tells the contractor what they’re building. Without being able to graphically communicate, you can’t get very far in the architecture profession. In data science, it’s the graphs and charts that make it into reports and presentations.
Another thing in common is in data science I’m looking at patterns and distributions. In architecture I’m always using proportions and symmetries to design spaces.
In both fields there is always more to learn.
I’m starting to think about my capstone project for the GA DSI now and will use this area to document some progress and to get some ideas out there.
I recently came across the idea of chaos in math. The example given was for modeling population, and depending on the growth rate, the equation could stabilize around and fluctuate between multiple numbers.
I have no idea how this will relate back to data science yet, but will explore further and see if there’s anything I can do with it. For now it’s just the beginnings of the beginning of an idea.
Tips that I learned this week (or recently since this is my first post):
Hit tab to auto-fill in Bash. It’s a gamechanger.
Control-click to edit multiple lines at the same time. Also a gamechanger.
In python, you can chain multiple .replace(‘str to replace’, ‘str to replace with or leave empty quotes’) to get rid of characters you don’t want.
Look at HTML in VS Code to make it a little more readable when searching through HTML formatted tables and data.