Erinevus lehekülje "Machine learning" redaktsioonide vahel
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== Lecture 3: K-means clustering, MLE principle == | == Lecture 3: K-means clustering, MLE principle == | ||
[[Meedia:Lecture3.pdf|Slides]] | [[Meedia:Lecture3.pdf|Slides]] | ||
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| + | [http://ciml.info/dl/v0_8/ciml-v0_8-ch02.pdf Reading I] | ||
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| + | [http://ciml.info/dl/v0_8/ciml-v0_8-ch13.pdf Reading II] | ||
== Lecture 4: Gaussian Mixture Model, EM algorithm == | == Lecture 4: Gaussian Mixture Model, EM algorithm == | ||
[[Meedia:Lecture4.pdf|Slides]] | [[Meedia:Lecture4.pdf|Slides]] | ||
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| + | [http://ciml.info/dl/v0_8/ciml-v0_8-ch14.pdf Reading] | ||
Redaktsioon: 5. märts 2014, kell 20:16
Spring 2013/2014
ITI8565: Machine learning
Taught by: Kairit Sirts
EAP: 6.0
Time and place: Fridays
Lectures: 16:00-17:30 X-406 Labs: 17:45-19:15 X-412
Additional information: sirts@ioc.ee, juhan.ernits@ttu.ee
The course is organised by the Department of Comptuer Science. The course is supported by IT Academy.
Students should also subscribe to machine learning list. This is used to spread information about the course in this semester as well as any other machine learning related event happening in TUT (also in future).
Lecture 1: Introduction, decision trees
Example made in class - When to play tennis?
Reading - contains also the full algorithm for decision tree learning with divide-and-conquer strategy.
First homework is open in moodle. For submitting you have to register to the course