Computer Science 470-001(4738) and 570-001(7550) at Northern Arizona University, Spring 2021
Topic: Artificial Intelligence.
Dates: 01/11/2021 - 05/07/2021.
Meeting time/place: MoWeFr 9:10AM - 10:00AM, SBS West, Rm 110. And on Zoom.
Course materials adapted from Dr. D’s Spring 2018 offering.
Syllabus: Google Doc.
Honors discussion group: Slack, Whenisgood Poll, Zoom meeting 6-7PM Thursdays.
Course evals due Apr 25!
For each programming project the input data file that you must use with your program will be posted here.
Please make sure that your report contains the commands and output as shown in this example output file. For each test command
- There should be a >>> prompt followed by the test command,
- followed by the output of that command (from print statements and/or the return value),
- followed by a newline (to provide visual separation between each command). If you do sys.ps1=’\n>>>’ then that will print a newline before every command prompt.
One way to do this is by simply running “python” which starts the interactive REPL, and then paste your code in. A more automated way to do this (less tedious copy-pasting) is by running your python script through interpreter.py.
It is recommended to separate your functions into two files, e.g.,
- project0_funs.py which defines the functions you need for your project.
- project0_tests.py which imports those functions and then runs the tests.
Then you can run the tests file through interpreter.py to get the required output, e.g.,
$ python interpreter.py project0_tests.py
>>> from project0_funs import *
>>> add(1, 2)
3
>>> add(3, 4)
7
Assignments are due in bblearn by 11:59PM on the indicated date. Grad project is only for CS570 students; other assignments are for all students.
- Week 1, Jan 11: First day of class exercise, Introduction video (to watch before next class), chapter 1 lecture (introduction and history).
- Week 2, Jan 18: Chapter 2 lecture (intelligent agents). Announcement about upcoming due dates (program 1, grad project proposal, Ch2 homework).
- Week 3, Jan 25: Program 1 Part 1 due Fri Jan 29. Grad project proposal due Weds Jan 27. Supplementary video lecture about search, demo of depth/breadth-first search.
- Week 4, Feb 1: Chapter 3 lecture. Ch2 Homework due Mon Feb 1. Program 1 Part 2 due Fri Feb 5.
- Week 5, Feb 8: Chapter 4 lecture.
- Week 6, Feb 15: Ch3 homework due Mon Feb 15. Grad project completed literature review due Weds Feb 17. Program 2 Part 1 due Fri Feb 19.
- Week 7, Feb 22: Chapter 19 lecture (supervised learning) slides. Program 2 Part 2 due Fri Feb 26.
- Week 8, Mar 1: Ch4 Homework due Mon Mar 1. Mid-term review, sample, and exam Fri Mar 5. More neural network and torch slides.
- Week 9, Mar 8: Grad project 5-10 minute presentation: guidelines, signup.
- Week 10, Mar 15: Program 3 part 1 due Sun Mar 21.
- Week 11, Mar 22: Chapter 5 lecture. Program 3 part 2 due Sun Mar 28.
- Week 12, Mar 29: Grad project draft paper due Fri Apr 2. Program 4 Phase 0 due Fri Apr 2.
- Week 13, Apr 5: Tkinter demo program, Another demo program, Program 4 Phase 1 due Fri Apr 9.
- Week 14, Apr 12: Program 4 Phase 2 due Fri Apr 16.
- Week 15, Apr 19: reading week – tournament + exam review.
- Week 16, Apr 26: finals week. Grad project final paper due.
The optional readings will be from Artificial Intelligence: A Modern Approach by Russell and Norvig.
- Dead tree book at Cline (on 4 hour reserve).
- Amazon
Tutorial explaining pytorch installation under anaconda.
The command I used to install was:
conda install pytorch torchvision cpuonly -c pytorchAfter that you should be able to do import torch in python.