Magpie is a deep learning tool for multi-label text classification. It learns on the training corpus to assign labels to arbitrary text and can be used to predict those labels on unknown data. It has been developed at CERN to assign subject categories to High Energy Physics abstracts and extract keywords from them.
A iPython notebook that introduces how to use the topicmodels module for implementing Latent Dirichlet Allocation using the collapsed Gibbs sampling algorithm of Griffiths and Steyvers (2004). The module contains three classes: one for processing raw text, another for implementing LDA, and another for querying. This tutorial will go through the main features of each, for full details see the documented source code.