Topics and Readings:
The schedule will be updated weekly, to reflect the plan on upcoming lectures, as well as provide slides and other material from the most recent lectures.
(Aug 29)
Introduction - The
basics
[pdf]
(Aug
31)
Introduction -
Design of a system (Ch.
1)
[pdf]
(Sep 7)
Concept Learning (Ch.2)
[pdf]
(Sep 12)
Decision Tres (Ch.3)
[pdf]
(Sept 14)
Bayesian Learning p.1
(Ch.6)
[pdf]
... and a probability
tutorial
[pdf]
(Sept
19)
Bayesian Learning p.2
(Ch.6)
[pdf]
.... except chapters 6.5, 6.6,
6.11, 6.12
(Sept
21)
Neural Networks I (Ch.
4)
[pdf]
(Sept
26)
Neural Networks II (Ch. 4)
[pdf]
(Oct
3)
Sampling - Evaluating algorithms
(Ch. 5)
[pdf]
(Oct 5)
Less naive classifiers
(Ch. 6)
[pdf]
(Oct
10)
Review
(Oct 12)
Review continued
and intro to PAC learning
[pdf]
(Oct 17)
PAC learning I (Ch.
7)
[pdf]
(Oct 17)
PAC learning II (Ch.
7)
[pdf]
(Oct
31)
Genetic Algorithms I (Ch.
9)
[pdf]
(Nov
2)
Genetic Algorithms II (Ch.
9)
[pdf]
(Nov 7)
Instance-Based
Learning (Ch. 8)
[pdf]
(Nov 23)
Reinforcement Learning
I (Ch. 13)
[pdf]
(Nov 28)
Reinforcement Learning
II (Ch. 13)
[pdf]