Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
Tools and recipes to train deep learning models and build services for NLP tasks such as text classification, semantic search ranking and recall fetching, cross-lingual information retrieval, and question answering etc.
Given a pair of questions on Quora, the NLP task aims to classify whether two given questions are duplicates or not. The underlying idea is to identify whether the pair of questions have the same intent though they might have been structured differently .
Examples of Natural Language Processing. Created at the Univeristy as the project within Natural Language Processing classes in 2015. The purpose of those examples was to get to know NLP techniques and using them in sample tasks like for example QA or polish surname variations app.
The methodology that was outline in the export.md is incredibly out-of-date. TensorFlow has official docker binaries now as well