Subject: Subject Sylbus: Machine Learning 1 - 096411 (Current)

Machine Learning 1 - 096411
Credit
Points
3.5
Given In
Semester
a
Lecture Exercise Laboratory Project or
Seminar
House
Work
Weekly
Hours
3 1 6
Possibility to guided reading

Determination of the grade according to progress during the semester and the submission of the final thesis


Prerequisites: ( Introduction to Statistics 094423
and Introduction to Computer Science H 234117 )
or ( Introduction to Statistics 094423
and Introduction to Computer Science N 234221 )
or ( Introduction to Statistics 094423
and Introduction to Computer Science 234111 )


Deal with Advanced Methods of Data Analsis and Will Cover Both Data, Visualization, Classification and Prediction. Specific Topics: Machine, Resampling, Model Selection and Regularization, Decision Trees and Regression. Cluster Analysis. Understanding the Theory of the Different Methods and Having the Ability to Apply It on Real Data.




Times and places of examinations 02/2020 2020/2021 Spring Semester
examination timedaydateSeason
Friday30.07.2021
Monday18.10.2021

Timetable to semester 02/2020 2020/2021 Spring Semester
RoomBuildingHourdayLecturerExercise
Lecture
no.Registering
Group
08:30-11:30TuesdayDoctor Garber DanLecture1011
08:30-09:30MondayExercise11
08:30-11:30TuesdayDoctor Garber DanLecture1012
12:30-13:30ThursdayExercise12


System of hours to the semesters
Semester Previous Semester information 01/2020 2020/2021 Winter Semester


Textbooks
PublishedPublisherAuthorsBook
1997prentice hallp. cabena, p. hadjnian and rolf p. cabena, p. hadjnian and rolfdiscovering data mining from concept to implementation
1996mcgraw-hilloj. p. bigusdata mining with neural networks: solving .business problems - from application dev. to dec

Created in 06/03/2021 Time 01:28:38