This class covers natural language processing, including both methods and well-known applications. Methods discussed will range from classical probabilistic methods such as Naive Bayes and Hidden Markov Models, to contemporary neural network methods, including word vector models, recurrent neural networks, and Transformer-based models. Applications discussed will include text classification, machine translation, and conversation systems (among others). Prerequisites: CS 515, Math 539 or 644 A preliminary syllabus can be found at: https://shcarton.github.io/cs780spring2023/