In many modern applications, data scientists face challenges which go beyond the basic techniques introduced in Data Mining I.
In this course we will cove advanced data mining techniques to handle large data volumes, volatile data streams and complex object descriptions. These topics (Volume, Velocity, Variety) comprise major challenges in Big Data analysis.
ECTS points: 4
- Big data challenges for data mining
- Mining over high dimensional data (feature selection, dimensionality reduction, high-dimensional clustering)
- Mining over large object cardinalities (parallel-, distributed-mining, summarization and sampling)
- Mining over data streams (stream classification, stream clustering, change detection)
- Multi-view and Multi-instance learning
- Lecture: every Thursday 10:00 - 11:30, starting 27.10.2016
- Tutorials: directly after the lecture, 11:45-12:30
- Room: 235 (3703), Appelstraße 4, 30167 Hannover
- Responsible Professor: Prof. Dr. Eirini Ntoutsi
- Teaching Assistants: Vasileios Iosifidis, Christoph Hube, Helge Holzmann, Ruben Hohndorf
!!! Please check Stud.IP for announcements, material and up-to-date information on the course.
!!! For live streaming use this link.