- A robust email and mailing address typo corrector for web forms.
- A Rickroll detecting browser plugin- it warns you before you follow a link that will likely result in Rickrolling. (Rickroll Protection As A Service?)
- A per-user clicktrail analyzer that predicts which links a user is most likely to follow, given their history. Use this to highlight or promote high-likelihood links.
- A user info and usage pattern analyzer that classifies users by likelihood of upgrading to a premium plan.
- A RubyGem for classifying user generated content into appropriate, inappropriate, spam, NSFW, etc.
- Along the same lines: a nudity detector for uploaded images.
- A RubyGem for code optimization based on the current backtrace, possibly using reinforcement learning. For example:
1 2 3 4 5 6 7 8 9 10
- A story karma predictor that estimates the final score on Hacker News of any article, based on textual content and the poster’s info.
- A system that classifies support requests by their estimated severity.
- Make things easier for your users:
- given them default settings selected by users similar to themselves
- default to pages they use often; expand modules they interact with frequently
Once you know what’s possible, it’s hard to find a project that wouldn’t benefit from some machine learning.
Have other ideas? Want to discuss these? Post them in the comments and follow @tectonic for updates.