https://wikicshse.ru/index.php?action=history&feed=atom&title=Introduction_to_Machine_Learning_and_Data_Mining_2020 2026-06-06T12:13:04Z История изменений этой страницы в вики MediaWiki 1.45.3 https://wikicshse.ru/index.php?title=Introduction_to_Machine_Learning_and_Data_Mining_2020&diff=362&oldid=prev 2020-02-16T05:59:16Z

<p>Migrated current public revision from wiki.cs.hse.ru</p> <p><b>Новая страница</b></p><div>&#039;&#039;&#039;Lecturer:&#039;&#039;&#039; Dmitry Ignatov<br /> <br /> &#039;&#039;&#039;TA:&#039;&#039;&#039; Dmitry Egurnov<br /> <br /> <br /> === Homeworks ===<br /> <br /> Homework 1: To be announced<br /> <br /> === Lecture on 16 Jan 2020===<br /> <br /> Intro slides. Course plan. Assessment criteria. ML&amp;DM libraries. What to read and watch?<br /> <br /> Practice: demonstration with Orange.<br /> <br /> === Lecture on 23 Jan 2020===<br /> <br /> Introduction to Clustering. Taxonomy of clustering methods. K-means. K-medoids. Fuzzy C-means. Types of distance metrics. Hierarchical clustering. <br /> <br /> Practice: demonstration with Orange.<br /> <br /> === Lecture on 30 Jan 2020===<br /> <br /> Introduction to Clustering (continued). Density-based techniques. DBScan and Mean-shift. <br /> <br /> Practice: demonstration with Orange and web-demo.<br /> <br /> === Practice on 6 Feb 2020 ===<br /> <br /> Clustering with scikit-learn (k-means, hierarchical clustering, DBScan, MeanShift, Spectral Clustering).<br /> <br /> === Lecture on 6 Feb 2020 ===<br /> <br /> Graph and spectral clustering. Min-cuts and normalized cuts. Laplacian matrix. Fiedler vector. Applications.<br /> <br /> === Practice on 13 Feb 2020 ===<br /> <br /> Clustering with scikit-learn (k-means, hierarchical clustering, DBScan, MeanShift, Spectral Clustering). Parameters tuning and results&#039; evaluation. Continued.</div>

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