Machine Learning and Data Mining
Introduction to Data Mining perspective; Association rules; Decision trees; Instance-based learning (nearest neighbors); Clustering; Support Vector machines (SVM); Evaluation (Train & Test, Cross-validation, Leaving-one-out); Data Streams.
Details
Code | 42032 62032 |
Type | Course |
ECTS | 5 |
Site | Neuchâtel |
Track(s) |
T4 – Theory and Logic T6 – Data Science |
Semester | A2023 |
Teaching
Learning Outcomes | The main objectives of this course is to introduce the students to the various techniques and strategies that can be used to
Practical exercises will complete the theoretical presentation. |
Lecturer(s) |
Christos Dimitrakakis |
Language | english |
Course Page | The course page in ILIAS can be found at https://ilias.unibe.ch/goto_ilias3_unibe_crs_2793354.html. |
Schedules and Rooms
Period | Weekly |
Schedule | Tuesday, 08:45 - 12:00 |
Location | UniNE, Unimail |
Room | B104 |
Additional information
Comment | First Lecture |