CS291K - Deep Learning for Text Mining and Understanding home | schedule


* April 6, Qualification Exam (In order to take this course, students need to pass this exam)

Abstract: This is a graduate-level course on deep learning for text ananlysis.  We will discuss newest publications on information extraction, question answering and dialog system.

Each student is expected to give one hour presentation and complete a research project.

Prerequisites: Neural network building experience or CS291K (spring 2016) or CS292F (spring 2017)

Enrollment Code: 08391 Instructor: Prof. Xifeng Yan , Email: xyan at cs.ucsb.edu

Time: Tuesday/Thursday 11:00- 12:50pm, Location: PHELP 3526   Office Hour:  Tuesday 1:00-2:00pm

TA: N/A.  Research Project Coordinator: Honglei Liu (liuhonglei at gmail dot com) and Keqian Li (keqianlicg at gmail dot com)


Grading: Your grade will be derived from paper presentation (20%),  project presentation  (15%), research project quality (50%), project report (15%) 

Text Books (not required, but you'd better read it)

Deep Learning, An MIT Press book, Ian Goodfellow and Yoshua Bengio and Aaron Courville

Lecture notes (will be available later)