First, the request for user feedback:
This blog has been around for almost six months, and gets quite a bit of traffic from various sources including twitter, reddit, dailykos, and organic search. It has branched in several directions, and if we based our future on prior traffic, we would create new posts around Kansas Political Issues and Data Science Toolkits.
But we want to be sensitive to our users real needs and wants. So, what would you like from us? If you have ideas, you can comment on this post or email to this address. For starters here are some examples of things we're considering looking at:
- Releasing player-level fantasy football ratings for 2015, based on our models from prior years that had good results. This would be along the same vein as our 2015 pre-season predictions.
- Continuing our analysis of Kansas education funding found here. We were kind of burned out with looking for data after this one, but this still seems to be relevant. Also, we have some overall methodological concerns with the 2006 study.
- Analysis of tax impact between sales and income tax? What is effective change to citizens with varying level of incomes.
- An update on how R in production is going. This would include server traffic, timing stats, and a summary of issues and resolutions we have encountered.
- A case study in how we create production-ified machine learning models, from start to finish.
- Early 2016 election predictions?
- More sports?
- More politics?
And for a preview, here's what is coming up later this week (for sure):
- Tuesday Jams: (of course, we have to have music) I don't want spoil it, but the band initials are DFD.
- Cumulative Fatigue: This is in our series on modeling fitness tracker data. After weeks of ramping up activity level using my Garmin fitness tracker (read: no days where I ran less than four miles since April 1), I hit the wall and my body fell apart. But can we predict when this will happen to prevent and use it in training plans?