Neural Machine Translation and Sequence-to-sequence Models: A Tutorial
It serves as an educational resource for learners aiming to understand and apply these models, but it is incremental as it focuses on explaining existing methods rather than presenting new research.
This tutorial introduces neural machine translation and sequence-to-sequence models as powerful techniques for handling sequential data, particularly in human language tasks, without assuming prior experience in neural networks or NLP.
This tutorial introduces a new and powerful set of techniques variously called "neural machine translation" or "neural sequence-to-sequence models". These techniques have been used in a number of tasks regarding the handling of human language, and can be a powerful tool in the toolbox of anyone who wants to model sequential data of some sort. The tutorial assumes that the reader knows the basics of math and programming, but does not assume any particular experience with neural networks or natural language processing. It attempts to explain the intuition behind the various methods covered, then delves into them with enough mathematical detail to understand them concretely, and culiminates with a suggestion for an implementation exercise, where readers can test that they understood the content in practice.