Podcast Listens Analysis
I’ve been telling everyone that I’d do something “data fun” when I hit 20K Twitter followers, so I posted an analysis of my podcast listeners! I used python and pandas in a Jupyter notebook for the first part, then I did a dashboard in Tableau for the last part.
Hi #DemystifyDS Attendees!
I’m assuming that some people who see my talk at Demystifying Data Science conference will be dropping by here, so I wanted to put up a quick post summarizing some of the resources I have made available to data science learners!
More silliness
Back before I had so many followers, and it was less stressful to put goofy stuff “in the wild”, I wrote data science parody lyrics to “Summer of ’69” and “For the Love of Money”. Well, a while ago, another idea popped into my head..
2 Quick Announcements
1. Sorry for the issues loading images and with logins on this site. I’ve had problems ever since I had bluehost set me up with HTTPS certificates, and apparently those certificates have expired or something and are causing issues with the images being able to load, etc. I’ll look into it, but I also have a busy week at work and wasn’t planning on site maintenance here this week, so it might be this way for a little bit. I am aware of it and a fix is on my to-do list, though! Thanks for your patience. 2. I published a post over on DataSciGuide about resources for data science beginners. Check it out! Thanks for your continued readership here! P.S. I’m working on the podcast again, so the 2 already-recorded episodes are back in the work pipeline...
Introductory Machine Learning Terminology with Food
I was just pondering some ways to discuss machine learning terminology in a way that would be accessible to beginners, and figured I’d share my semi-thought-out ideas here. I’m sure this has been done before, but here are some common machine learning terms couched in the language of cooking and food. Feedback welcome!
Machine Learning Algorithm
A machine learning algorithm is a list of instructions to guide a computer to analyze some data to find patterns, and works much like a cooking recipe. You put some data in (ingredients), do some stuff to it (preparation and cooking), and then evaluate how the results compare to what you were hoping to accomplish (photo in your cookbook and expectations of taste).