Key Information
About the content
Have you ever wondered how to build a system that automatically translates between languages? Or a system that can understand natural language instructions from a human? This class will cover the fundamentals of mathematical and computational models of language, and the application of these models to key problems in natural language processing.
Syllabus
1. Language modeling.
2. Hidden Markov models, and tagging problems.
3. Probabilistic context-free grammars, and the parsing problem.
4. Statistical approaches to machine translation.
5. Log-linear models, and their application to NLP problems.
6. Unsupervised and semi-supervised learning in NLP.
Instructors
- Michael Collins
Content Designer
Columbia University is a private university located in Morningside Heights, in the north-western part of the borough of Manhattan, in New York (United States). Its origins lie in King's College, founded in 1754 by King George II of Great Britain. It is one of the oldest institutions of higher learning in the United States and is part of the Ivy League group of eight of the country's oldest, most famous, most prestigious and most elitist universities.
Columbia is one of the most selective and prestigious universities in the world. The admission rate was 5.1% in 2019, comparable to Harvard and Stanford. Ranked first in the United States for research, it is sixth in the world (fourth in the United States) in the CUWR ranking of the world's top 1,000 universities and eighth in the Shanghai University Rankings.
Platform
Coursera is a digital company offering massive open online course founded by computer teachers Andrew Ng and Daphne Koller Stanford University, located in Mountain View, California.
Coursera works with top universities and organizations to make some of their courses available online, and offers courses in many subjects, including: physics, engineering, humanities, medicine, biology, social sciences, mathematics, business, computer science, digital marketing, data science, and other subjects.
