This is a graduate course in computer science, studying topics in natural Language processing. This course covers core-level natural language processing such as part-of-speech tagging, named entity recognition, dependency parsing, semantic role labeling, and coreference resolution as well as their real world applications such as sentiment analysis, question answering, etc. Recent advances in machine learning (e.g., adaptive gradient descent, structured prediction, neural networks) and natural language processing (e.g., distributional semantics, abstract meaning representation) will also be discussed.

• Syllabus.
• Schedule.
• Reading.
• Quizzes.