11-731 Machine Translation and Sequence-to-Sequence Models

12 units, Carnegie Mellon University

Instructors Graham Neubig. Prerequisites This course has no official prerequisites, although 11711 Algorithms for NLP or 10701 Machine Learning would be helpful. Course Description Machine Translation and SequencetoSequence Models is an introductory graduatelevel course surveying the primary approaches and methods for developing systems to translate between human languages, or other sequential data. The main objective of the course is to obtain basic understanding and implementation skills for modern methods for MT and sequence transduction, including how to design models, how to learn the model parameters, how to search for the best output, and how to create training data. The course will focus on machine translation, but also briefly cover tasks such as dialog response generation, image caption generation, and others.

Prerequisites: none listed

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