CAP 6619: Deep Learning

Announcement

(The content of this page changes frequently)

Class Time: 2018 Fall, Tuesday & Thursday, 2:00 PM - 3:20PM
Classroom: TBD
Office Hour: 2018 Fall, Tuesday & Thursday, 9:00AM - 11:00AM & 1:00PM - 2:00PM

Textbook:

Deep Learning , Ian Goodfellow, Yoshua Bengio, and Aaron Courville, The MIT Press, 2016

Reference books:

Neural Networks for Pattern Recognition , Christopher M. Bishop, Clarendon Press, 1996 (Online version available)
Pattern Recognition and Machine Learning Christopher M. Bishop, Springer, October, 2007, (Online version available)

Course Description:

This course teaches students basic concepts of deep learning, with an application in engineering, business and other areas. The class will cover three major topics including deep learning theory, implementation, and applications. Topics include math preliminaries, machine learning basics, deep forward networks, convolution networks, autoencoders, representation learning networks, their implementations and applications.

Topics:

Introduction

Linear Algebra Basics
Optimization Basics

Intro. to Neural Network Learning

Single Layer Perceptrons
Multilayer Perceptrons
Support Vector Machines

Deep Neural Networks

Deep Forward Networks
Convolutional Networks
Auto encoder Learning
Reprsentation Learning Networks

Deep Learning Applications

Lectures, Assignments, and Projects

Course lectures, assigments, etc. are announced through Canvas
Resources
Dataset
Project

Grading policy:

Homework (including Project)	65
Final Examination	30
Participation	5

Your final grade will be based on the scores you have earned from the above categories (compared to the performance of other students in the class).

Late policy:

All assignments are due midnight on the assigned due date. Please refer to the Assignments and Projects for details on submission. Late submission is allowable, however, the late penalty is -2pts/day.

Communication:

All important course announcement and communication will be done through Canvas. When communicate through emails, please use your fau.edu email address. Sending email to me from another account is disencouraged, and if you do you must set the reply-to field to your FAU email account if the message concerns grading or evaluation in any way. Please include course code CAP5615 and your name in all messages concerning the course.

All work in this course must be INVIDUAL effort unless specified otherwise.