CSE 244B Machine Learning for Natural Language Processing

Introduction to machine learning models and algorithms for Natural Language Processing. Covers deep learning approaches and traditional machine learning models. Topics include an introduction to standard neural network learning methods such as feed-forward neural networks, recurrent neural networks, convolutional neural networks, and encoder-decoder models with applications to natural language processing problems such as utterance classification and sequence tagging. Requirements include a midterm, final, programming assignments, and a project. (CSE 244A and CSE 244B formerly offered as one course, CSE 244.)