Natural Language Understanding with Distributed Representation
Computation and Language
2015-11-26 v1 Machine Learning
Abstract
This is a lecture note for the course DS-GA 3001 <Natural Language Understanding with Distributed Representation> at the Center for Data Science , New York University in Fall, 2015. As the name of the course suggests, this lecture note introduces readers to a neural network based approach to natural language understanding/processing. In order to make it as self-contained as possible, I spend much time on describing basics of machine learning and neural networks, only after which how they are used for natural languages is introduced. On the language front, I almost solely focus on language modelling and machine translation, two of which I personally find most fascinating and most fundamental to natural language understanding.
Cite
@article{arxiv.1511.07916,
title = {Natural Language Understanding with Distributed Representation},
author = {Kyunghyun Cho},
journal= {arXiv preprint arXiv:1511.07916},
year = {2015}
}