|
|
|||||||||||||||||
Course Catalog 2014-2015
SGN-42006 Machine Learning, 5 cr
|
Lessons
| Study type | P1 | P2 | P3 | P4 | Summer | Lecture times and places |
|
|
|
|
|
|
|
|
Description:
. Learning outcomes: The student can describe the difference artificial intelligence and machine learning. The student can list the mentioned learning rules. The student can describe them and is capable to apply them to train neural networks. The student is capable to list to analyse the lectured neural networks (MLP,SVM,SOM and recurrent networks). The student is capable to analyse the own problem and to select the most suitable, lectured neural network. The student has a certain capability to create new solutions based on the lectured material.
Person responsible:
Ari Visa
Assessment scale:
Numerical evaluation scale (1-5) will be used on the course
Additional information of course implementation:
. Lecturer:............Professor Ari Visa, ari.visa@tut.fi, room TF309, phone 040 728 7969 Requirements:...The examination is based on the final exam and active participation in classroom exercises. Exercises:.........are held by M.Sc. Katariina Mahkonen, email: katariina.mahkonen@tut.fi, room: TF317 Literature:..........Neural Networks: a Comprehensive Foundation, Simon Haykin, 2nd Ed. Prentice-Hall Inc., 1999.