10. Introduction to Learning, Nearest Neighbors

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MIT 6.034 Artificial Intelligence, Fall 2010
View the complete course: http://ocw.mit.edu/6-034F10
Instructor: Patrick Winston

This lecture begins with a high-level view of learning, then covers nearest neighbors using several graphical examples. We then discuss how to learn motor skills such as bouncing a tennis ball, and consider the effects of sleep deprivation.

License: Creative Commons BY-NC-SA
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More courses at http://ocw.mit.edu

Comments

Eli Vázquez says:

Thank you Patrick Winston !

Tùng Nguyễn_Trọng says:

The sleep data is helpful to me. This Professor is very typical of how a Robotics Prof. would teach.

E M says:

46:06 Another thing that is not especially related to the topic is that even when deprived of sleep, the brain works better in the middle of the day rather then the start or end. The huge drops of performance happens when a "subject" is used to sleep/need to sleep. While performance doesn't drop at all (and even goes higher related to the "sleeping time") during the mid-day. Therefore Linear regression can tell you the obvious hypothesis (losing sleep = losing performance) While the Cubic spline can teach you new things you didn't even think of.

Mudit Verma says:

Amazing teacher !

0 1 says:

The last minute of the lecture is gold.

2flight says:

Thanks Patrick Winston for the lively presentations! Thanks MIT!!!

Cheng-Hao Chang says:

The world is better with you, thanks prof Winston and MIT

Spas says:

The deeper you go into the series the more hard-core programmers you meet in the comment section 😀

Heng Yue says:

i can't imagine how much does the knowledge contained in this course worth.

3210jr says:

Amazing lecturer!

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