Mining Massive Data Sets 2025
Section outline
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The lectures @FRI will take place on Fridays at 14:15 in P03.
Orodja za analizo velikih podatkovnih baz
Obravnavali bomo algoritme podatkovnega rudarjenja in strojnega učenja za analizo zelo velikih količin podatkov. Predmet se izvaja vzporedno s predmetom Mining massive data sets na Stanford University (prof. Jure Leskovec).
Mining massive data sets
The course will discuss data mining and machine learning algorithms for analyzing very large amounts of data.
Topics include:
MapReduce and Spark; Frequent Itemsets and Association Rules; Locality-Sensitive Hashing; Clustering; Dimensionality reduction; Recommender Systems; Link Analysis: PageRank & Extensions); Community Detection in Graphs; Learning Embeddings; Graph Representation Learning; Graph Neural Networks; Large-Scale Supervised Machine Learning; Mining Data Streams; Computational Advertising; Optimizing Submodular Functions; Multi-Armed Bandits
Assignments and grading:
- 4 homework assignments requiring coding and theory (40%)
- Final exam (30%)
- Weekly Colab notebooks (30%)
Useful links:
- Course website: http://web.stanford.edu/class/cs246/
- Handouts (PDF): http://web.stanford.edu/class/cs246/handouts/CS246_Info_Handout.pdf
- Reference book: http://www.mmds.org/
All deadlines at FRI are exactly the same as Stanford deadlines.