IP (A) (Tools for Large Database Analysis)
Week | Name | Description |
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Videos | username: snap, password: cs246-videos-2025 |
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username: snap, password: cs246-videos-2024 |
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username: snap, password: cs246-spring2023-videoarchive |
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username: cs246, password: mining2022 |
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Prosojnice in dodatna gradiva / Slides and supplementary materials | This Jupyter notebook is based on the lecture "CS246: Mining Massive Datasets: Crash Course in Spark" by Daniel Templeton. |
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This Jupyter notebook is based on the book Machine Learning in Action by Peter Harrington (Manning Publications, 2012). |
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This document provides a clear, step-by-step explanation of the PCY algorithm, demonstrating its ability to prune candidate pairs by using a compact dataset and a simple hash function. |
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Potrebe po izboljšanju odkrivanja skupin vedno bolj zahtevajo možnost interakcije z domenskimi eksperti, kar je vodilo do razvoja algoritmov odkrivanja skupin z omejitvami (angl. constrained clustering). Ti algoritmi uporabljajo domensko znanje v obliki pozitivnih (angl. must-link) in negativnih omejitev (angl. cannot-link) na pare učnih primerov, kar omogoča izboljšanje procesa odkrivanja skupin... |
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A template for the hubs-and-authorities algorithm - HITS (hyperlink-induced topic search). |
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V magistrskem delu, ki je rezultiralo v objavi spodnjega članka v ugledni znanstveni reviji Mathematics, uporabimo moderne pristope strojnega učenja na grafih za pohitritev dinamičnega algoritma za iskanje maksimalne klike. Kristjan Reba, Matej Guid, Kati Rozman, Dušanka Janežič, and Janez Konc. Exact maximum clique algorithm for different graph types using machine learning. Mathematics 10, no. 1 (2022): 97. |
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avtor William L. Hamilton, McGill University |
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Videoposnetki pri predmetu CS224W: Machine Learning with Graphs na Stanford University, ki ga vodi in poučuje prof. Jure Leskovec. |
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Homework Submissions | ||
Exam | ||
See the "Final Exam Review Session" lecture in the Winter Course 2022. |
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