I trained a model to predict if a given post will reach the front page, get flagged etc, I collected over a 1000 RSS feeds and rank the RSS entries with my ranking models.
I submit the high ranking entries on HN to test out my models and I can reach the front page consistently sometimes having multiple entries on the front page at a given time.
I also experiment with user->content recommendation, for that I use comment data for modeling interactions between users and entries, which seems to work fine.
Only problem I have is that I get a lot of 'out of distribution' content in my RSS feeds which causes my ranking models to get 'confused' for this I trained models to predict if a given entry belongs HN or not. On top of that I have some tagging models trained on data I scraped from lobste.rs and hand annotated.
I had been working on this on and off for the last 2 years or so, this account is not my main, and just one I created for testing.
AMA