CS 4620,  Intelligent Systems

Spring 2017

Instructor: Dr. Ben Schafer

 

The following links may be helpful this semester.
Date Day Type  Due at the start of class unless otherwise noted
1/9 Start of Class  
1/11 RD Reading Set #1 - Intelligent/Expert Systems
1/13 Discussion - Ideas Come with ideas for projects
1/16 MLK Holiday No Class
1/18 Discussion - Ideas

Deliverable #0 - Email me with two specific project ideas.

1/20 GP Deliverable #1 - Team Formation due by end of class
1/23 GP  
1/25 GP Deliverable #2 - Reading Suggestions (due at end of class)
1/27 GP - Work with your RD team Deliverable #3 - Initial Project Analysis (email a pdf to me by 5:00 PM)
1/30 RD - Intro to Deep Learning  
2/1 RD - Genetic Algirthm Techniques  
2/3 RD - Recurrent Neural Networks Some Suggestions at this stage of the game
2/6 RD - Text Analytics  
2/8 RD - Monte Carlo Tree Methods  
2/10 Extra Reading Set - Sprint and Scrum Deliverable #4 - Formal Project Proposal
2/13 Kickoff - Sprint #1  
2/15 GP

2/17 GP  
2/20 GP  
2/22 Tensor Flow Lecture (slides) (Jupyter notebook with Ryan's examples)  
2/24 DC of Sprint #1 Deliverable #5 - Sprint Report
2/27 Kickoff - Sprint #2  
3/1 GP  
3/3 GP  
3/6 GP  
3/8 GP  
3/10 DC of Sprint #2 Deliverable #6 - Sprint Report
3/20 Kickoff - Sprint #3  
3/22 GP  
3/24 GP  
3/27 GP  
3/29 GP  
3/31 DC of Sprint #3 Deliverable #7 - Sprint Report
4/3 Kickoff - Sprint #4  
4/5 GP  
4/7 GP  
4/10 GP  
4/12 GP  
4/14 DC of Sprint #4 Deliverable #8 - Sprint Report
4/17 Kickoff - Sprint #5  
4/19 GP  
4/21 GP  
4/24 GP  
4/26 GP  
4/28 GP Deliverable #9 - Final Project (Part A)  (Part B)
5/1

Deliverable #10:

10:00-11:50, Final Meeting (What you will do as an audience member)