Paris Machine Learning #1 Season 5: Code Mining, Mangas, Drug Discovery, Open Law, RAMP

This involves automatic extraction of the business logic from a code base. One of the challenges is to understand the developper's intentions that led to a specific organization of this business logic. Using Posters to Recommend Anime and Mangas by Jill-Jênn Vie, (livestream from Japan) - English- The classic recommendation problem is the following: given a user and the items (mangas) that they like, how can we recommend new items (mangas) that they are also likely to enjoy? Typically this is done via collaborative filtering, i.e. people with similar taste also enjoy other mangas, so we recommend these to the original user. A very common problem occurs when you have a new or obscure manga, aka the cold-start problem. There are no reviews to use for this manga, so a cooler option is to build a system that actually understands the content it recommends. We propose extracting visual information from the posters of these little-known mangas, using a deep neural net called Illustration2Vec. The theory is that users that like mangas with "girl with sword" will also like other mangas that have "girl with sword" or perhaps "girl with bow" but probably not "multiple boys in a swimming pool".