CS 662 Resources


Announcements:

Topics for the final exam are now available.

Here are some extra FOL questions for you to practice with.

Topics for midterm 2 are now available.

Topics for midterm 1 are now available.

A Sample midterm 1 is now available. Answers are here.

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Regrading:

If you feel that your homework was not graded correctly, you should return it to me, along with a written explanation of the error. I will evaluate this explanation and award any necessary points.


Lectures and associated readings:
Date Topic Associated Reading Slides
August 23 Lecture 1: Introduction. What is AI? R & N: 1.1 pp 1-4, 26.1-2: pp 947-958 Full size
Printable
August 28 Lecture 2: Intro to Python Dive Into Python Chapters 2,3,6. Full size
Printable
August 30 Lecture 3: Agents and Environments R & N: Chapter 2: pp 32-58 Full size
Printable
September 4 Lecture 4: More Python Dive Into Python Chapters 4,5,8. Full size
Printable
September 6 Lecture 5: Search I: BFS, DFS, IDS R & N: 3.1-3.5 pp 59-83 Full size
Printable
September 11 Lecture 6: Search II: Greedy Search, A* R & N: 4.1-4.2 pp 94-109 Full size
Printable
September 13 Lecture 7: Intro to Information Retrieval R & N: 23.2 pp 840-848
Baeza-Yates & Ribero-Neto: 2.5 (provided in class)
Full size
Printable
September 18 Lecture 8: Intro to Natural Language Processing R & N: 22.2-22.5 pp 795-818 Full size
Printable
September 20 Lecture 9: Statistical NLP R & N: : 23.1, 23.3 pp 834-840, 848-850
Manning and Schütze, Ch 11,12 (provided in class)
Full size
Printable
September 25 Lecture 10: Introduction to Knowledge Representation R & N: 7.1-7.5: pp 194-220 Full size
Printable
September 27 Midterm 1
October 2 Lecture 11: First-order Logic R & N: 8.1-8.3: pp 240-258 Full size
Printable
October 4 Lecture 12: Inference and Rule-based systems R & N: 9.1-9.6: pp 272-300
October 9 Lecture 13: Ontologies R & N: 10.1, 10.2, 10.5, 10.6. pp 320-328, 344-354. Full size
Printable
October 11 Lecture 14: More ontologies Ontology Development 101
The Pizza Ontology Tutorial
October 16 Lecture 15: Planning I R & N: 11.1-11.3: pp 375-395 Full size
Printable
October 19 Lecture 16: Planning II R & N: 12.2-12.6: pp 422-449 Full size
Printable
October 23 Lecture 17: Decision Trees R & N 18.1-18.3. pp 649-664. Full size
Printable
October 25 Lecture 18: Probability I R & N 13.1-13.6: pp 462-481 Full size
Printable
October 30 Lecture 19: Probability II R & N 14.1, 14.2: pp 492-499. Full size
Printable
November 1 Lecture 20: Bayesian Learning R & N 20.1: pp 712-716 Full size
Printable
November 6 Midterm II n/a
November 8 Lecture 21: Utility and Value of Information R & N 16.1-16.3, 16.6: pp 584-591,600-603 Full size
Printable
November 13 Lecture 22: Markov Decision Processes R & N: 17.1-17.3: pp 613-625 Full size
Printable
November 15 Lecture 22: Markov Decision Processes R & N: 17.1-17.3: pp 613-625 Full size
Printable
November 20 Lecture 24: Clustering Algorithms R & N: 20.1, 20.4, 21.1: 712-716, 733-736, 763-765 Full size
Printable
November 22 Thanksgiving. No class n/a
November 27 Lecture 25: Reinforcement Learning R & N 21.1-21.3: pp 763-777 Full size
Printable
November 29 Lecture 26: Neural Networks I R & N 20.5: 736-748 Full size
Printable
December 4 Lecture 27: Neural Networks II R & N 20.5: 736-748 Full size
Printable

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