Deep Learning and Neural Networks

Advanced Research Seminar I/III
Graduate School of Information Science
Nara Institute of Science and Technology
January 2014


Kevin Duh, IS Building Room A-705
Office hours: after class, or appointment by email ( where x=kevinduh)

Course Description

Deep Learning is a family of methods that exploits using deep architectures to learn high-level feature representations from data. Recently, these methods have helped researchers achieve impressive results in various fields within Artificial Intelligence, such as speech recognition, computer vision, and natural language processing. This course provides an overview of Deep Learning and Neural Networks; the goal is to establish a foundational understanding at a level sufficient for students to start reading research papers in this exciting and growing area.

Prerequisites: basic calculus, probability, linear algebra.

Course Schedule

Jan 14, 16, 21, 23 (9:20-10:50am) @ IS Building Room L2

Two video options are available: [1] Video (HD) includes slide synchronization and requires Adobe Flash Player version 10 or above. [2] Video (Youtube) may be faster to load and is recommended if you have trouble with Video (HD).

If you find errors, typos, or bugs in the slides/video, please let me know.

Useful References

  1. Short surveys and tutorials:
  2. In-depth lectures and books:
  3. To go even deeper:

Last modified: Thu Feb 6 18:14:26 JST 2014