Mining Massive Data Sets
Schedule: This course starts in the beginning of January. We will follow a weekly schedule which means that you will also have to do homework assignment during exam break.
The course will discuss data mining and machine learning algorithms for analyzing very large amounts of data. The emphasis will be on Map Reduce as a tool for creating parallel algorithms that can process very large amounts of data.
Topics include: Frequent itemsets and Association rules, Near Neighbor Search in High Dimensional Data, Locality Sensitive Hashing (LSH), Dimensionality reduction, Recommendation Systems, Clustering, Link Analysis (PageRank), Large scale supervised machine learning, Data streams, Mining the Web for Structured Data, Relation extraction and Web Advertising.
Term of implementation: 7. 1. 2020 to 12. 3. 2020.
- nosilec: Matej Guid