Deep Learning for Natural Language Understanding (LIGN 167)


An introduction to neural network methods for analyzing linguistic data. Basic neural network architectures and optimization through backpropagation and stochastic gradient descent. Word vectors and recurrent neural networks, and their uses and limitations in modeling the structure of natural language.

Prerequisites:
  • MATH 10C or MATH 20C or MATH 31BH
  • No linguistics background required

Quarter: Fall 2018
Days: Tuesdays & Thursdays
Time: 5:00 pm – 6:20 pm
Location: Center 105
Instructor: Prof. Leon Bergen

If you have any questions about the course, please contact Prof. Leon Bergen (lbergen@ucsd.edu)