Erinevus lehekülje "Machine learning" redaktsioonide vahel
86. rida: | 86. rida: | ||
[[Media: Lecture9_Practice.zip|Data file for the practice]] | [[Media: Lecture9_Practice.zip|Data file for the practice]] | ||
+ | |||
+ | |||
+ | == Lecture 10: Neural networks == | ||
+ | [[Media:Neural Network Presentation for Machine Learning Class.pdf |Slides]] | ||
+ | |||
+ | |||
+ | == Lecture 11: Multiclass classification == | ||
+ | [[Media:Lecture11_ML2015_N_Multiclass_classification |Slides]] |
Redaktsioon: 16. aprill 2015, kell 11:01
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