What does critical data science add to our understanding of sexual harassment in academia? [more inside]
Just finished building a content recommendation engine for MeFi using natural language processing and non-negative matrix factorization techniques! It produces a list of post recommendations based on a user history of posts, comments and favorites. It can also make recommendations based on a piece of text, so for example, you could paste a particular post and it will return a list of other posts that have some similar characteristics. I hope you enjoy playing around with it! Please let me know what you think. Here's more info in case you're interested (: https://github.com/tomasbielskis/metafilterpostrecommender
Monolog is an interactive diary bot that prompts you with interesting questions, which it chooses based on the topics you write about. [more inside]
A twitter bot that uses machine learning to define invented words, posting truncated definitions on Twitter and complete ones on Tumblr. Tweet @lexiconjure a made-up word, and it'll define it for you. [more inside]
Neuralsnap generates an image caption using a model I trained (convolutional and recurrent neural networks), then uses another character-level recurrent neural net that I trained on ~40 MB of poetry to expand the caption into a poem. (In this example, generated from a Rothko painting, the red text is the direct image caption, and the rest is the poetic expansion.) [more inside]
Using Python 2.7 and the Natural Language Toolkit, I created a program called Sonnetizer that generates 14-line rhyming sonnets in (mostly) iambic pentameter from any text corpus. Using Sonnetizer, I generated 10,000 unique sonnets from the sonnets of William Shakespeare, and compiled them into a PDF.