The simplest thing would be to just give people that list of tips from the beginning of the article. That would help them find the best photo a lot easier than

The simplest thing would be to just give people that list of tips from the beginning of the article. That would help them find the best photo a lot easier than this. There's also a lot of studies from ok cupid on profile picture optimization. Second, how many people get enough matches to get any statistically useful information? The people that need this the most are the least likely to benefit. Third, epsilon greedy isn't the best algorithm to use. Thompson sampling is theoretically optimal, and pretty simple. Here is a cool simulation of it in your browser. I find it fun to play with (sadly the graphs no longer render properly on this archived version. I have no idea why. But it used to display a beta distribution for each bandit, and you could see it shrink over time.): http://web.archive.org/web/20160310000407/https://e76d6ebf22ef8d7e079810f3d1f82ba1e5f145d5.googledrive.com/host/0B2GQktu-wcTiWDB2R2t2a2tMUG8/ http://web.archive.org/web/20160310000407/https://e76d6ebf22... Lastly it would be interesting to train a neural network to predict how good a profile picture is. This has sort of been done by Karpathy here: http://karpathy.github.io/2015/10/25/selfie/ http://karpathy.github.io/2015/10/25/selfie/ Tindr has an enormous amount of data that could be used.