Erinevus lehekülje "Machine learning" redaktsioonide vahel
| 115. rida: | 115. rida: | ||
[[Media:HomeAssignment_4.zip |Data]] | [[Media:HomeAssignment_4.zip |Data]] | ||
| − | ==Guest | + | ==Guest Lecture== |
| − | + | ||
[[Media:SVM_MK_2015.pdf |Support vector Machines by Maria Kesa]] | [[Media:SVM_MK_2015.pdf |Support vector Machines by Maria Kesa]] | ||
Redaktsioon: 20. mai 2015, kell 16:49
Previous years: 2014
Spring 2014/2015
ITI8565: Machine learning
Taught by: Sven Nõmm
EAP: 6.0
Time and place: Thursdays
Lectures: 14:00-15:30 ICT-A2 Labs: 16:00-17:30 ICT-405
Consultation: by appointment
Additional information: sven.nomm@ttu.ee
The course is organised by the Department of Comptuer Science. The course is supported by IT Academy.
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.
Lecture 2: k-nearest neighbors
Data file for the practice Reading
Lecture 3: K-means & Gaussians
NB! Home assignment Nr.1 will be given next week
Lecture 4: Gaussian Mixture Model & EM algorithm
Home assignment Nr.1 If you missed the class please contact the lecturer sven.nomm@gmail.com to receive your individual data and get assignment for the part 2.1.
Lecture 5: Linear Regression
Lecture 6: Logistic Regression
Home Assignment 1: Grades
Lecture 7: Logistic Regression
Home assignment Nr.2 If you missed the class please contact the lecturer sven.nomm@gmail.com to receive your individual data.
Lecture 8: Artificial neural networks
Lecture 9: Competitive learning
Lecture 10: Neural networks
Lecture 11: Multiclass classification
Home Assignment 3: Neural networks
Lecture 13
NB! Thursday 30.04.2015 Lecture is cancelled!!! Instead of the lecture practice will take place at 14:00 ICT-405 !!!
Final Project: description
Home Assignment 4
Guest Lecture
Support vector Machines by Maria Kesa
Consultation
21.05.2015 ICT-405 14:00- 17:30