Seminar on Machine Learning Rada Mihalcea. Introduction to Machine Learning Administrivia January 13(!), 2004. Machine Learning?. Definition:
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
Introduction to Machine Learning
January 13(!), 2004
A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience.
Learning: improving with experience at some task
Example: Learn to play checkers:
m3 : bb3
m2 : bb2
m1 : bb1State Space Search
V(b)= maxi V(bi)
V(b1)= mini V(bi)
m6 : bb6
m5 : bb5
m4 : bb4
Black wins: V(b)=-100
Blue wins: V(b)=100
#board states < 8!*22/(2!*2!*4!) = 1680
Regular checkers (8x8 board, 8 pieces each)
#board states < 32!*216/(8! * 8! * 16!)= 5.07*1017
Need to decide upon topic in four-six weeks from today.