I've been working on forecasting NHL games at nhlforecasts.com.
It's been a fun challenge as the games are pretty clustered in terms of scoring, and the games themselves are random with minimal points scored. I'm also not the biggest fan of hockey, so it's been fun for me to see which teams are ranked high.
I've been leaning on AI for the first time which has been interesting; I see a ton of content with AI around web dev, but less around more data science. It's interesting how quickly AI will break a common sense rule, like data leakage. Really fun learning experience!
In terms of platform, I've been having a ton of fun with static sites. Cheaper to host and more secure, all I need is a domain name to get it accessible on the web.
For a more data science-y project, I'm having a blast building https://nhlforecasts.com. I live in a town with a hockey team, and figured the best way to become a fan would be to understand the sport from a data driven approach.
I did a ton of work on building an Elo model first, but was getting very compressed results in terms of postseason predictions. I swapped to a Bayesian approach which has really taken off. Not sure how it's going to handle the second round of games approaching, but that's a problem for the future!
It's been a fun challenge as the games are pretty clustered in terms of scoring, and the games themselves are random with minimal points scored. I'm also not the biggest fan of hockey, so it's been fun for me to see which teams are ranked high.
I've been leaning on AI for the first time which has been interesting; I see a ton of content with AI around web dev, but less around more data science. It's interesting how quickly AI will break a common sense rule, like data leakage. Really fun learning experience!
In terms of platform, I've been having a ton of fun with static sites. Cheaper to host and more secure, all I need is a domain name to get it accessible on the web.