| Entrambe le parti precedenti la revisioneRevisione precedente | |
| magistraleinformatica:dmi:start [19/02/2026 alle 14:03 (7 settimane fa)] – Anna Monreale | magistraleinformatica:dmi:start [19/02/2026 alle 14:10 (7 settimane fa)] (versione attuale) – Anna Monreale |
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| |23. | 14.11 | Exercises: DT simulation, CLustering, sequences | {{ :magistraleinformatica:dmi:dt-learning-simulation.pdf |}} {{ :magistraleinformatica:dmi:learnedtree.pdf |}}{{ :magistraleinformatica:dmi:2025-ex-clustering.pdf |}} {{ :magistraleinformatica:dmi:ex-sequences.pdf |}}| | Monreale | | |23. | 14.11 | Exercises: DT simulation, CLustering, sequences | {{ :magistraleinformatica:dmi:dt-learning-simulation.pdf |}} {{ :magistraleinformatica:dmi:learnedtree.pdf |}}{{ :magistraleinformatica:dmi:2025-ex-clustering.pdf |}} {{ :magistraleinformatica:dmi:ex-sequences.pdf |}}| | Monreale | |
| |24. | 18.11 | Advanced Decision Trees, GAMs, and ensemble models | {{ https://github.com/data-mining-UniPI/teaching25/blob/lectures/machine%20learning/Supervised%20tasks.html.pdf | Slides }} | | Setzu | | |24. | 18.11 | Advanced Decision Trees, GAMs, and ensemble models | {{ https://github.com/data-mining-UniPI/teaching25/blob/lectures/machine%20learning/Supervised%20tasks.html.pdf | Slides }} | | Setzu | |
| |25. | 25.11 | Neural networks | {{ https://github.com/data-mining-UniPI/teaching25/blob/lectures/machine%20learning/Networks.pdf | Slides }} | | Setzu | | |25. | 19.11 | Project Presentations | | |Setzu, Monreale | |
| |26. | 26.11 | Time series, Python Supervised Learning & Imbalanced Scenarios | {{ https://github.com/data-mining-UniPI/teaching25/blob/lectures/time%20series/Time%20series.html.pdf | Slides }} {{ :magistraleinformatica:dmi:supervised_learning.zip |}} {{ :magistraleinformatica:dmi:data_notebook.zip |}} | | Setzu, Mannocci | | |26. | 20.11 | Project Presentations | | |Setzu, Monreale | |
| |27. | 27.11 | Time series, Python Supervised Learning & Imbalanced Scenarios | {{ https://github.com/data-mining-UniPI/teaching25/blob/lectures/time%20series/Time%20series.html.pdf | Slides }}, {{ https://github.com/data-mining-UniPI/teaching25/blob/lectures/time%20series/Time%20series.html | Slides in HTML (w/ working animation) }} | | Setzu | | |27. | 25.11 | Neural networks | {{ https://github.com/data-mining-UniPI/teaching25/blob/lectures/machine%20learning/Networks.pdf | Slides }} | | Setzu | |
| |28. | 02.12 | Shapelet-based Classification, Motif discovery | {{ :magistraleinformatica:dmi:23_time_series_motif-shapelets2023.pdf |Slides}} | {{ :magistraleinformatica:dmi:shaplet.pdf |}} {{ :magistraleinformatica:dmi:matrixprofile.pdf |}} [[https://www.cs.ucr.edu/~eamonn/MatrixProfile.html|Papers and resourse on motif]] |Monreale | | |28. | 26.11 | Time series, Python Supervised Learning & Imbalanced Scenarios | {{ https://github.com/data-mining-UniPI/teaching25/blob/lectures/time%20series/Time%20series.html.pdf | Slides }} {{ :magistraleinformatica:dmi:supervised_learning.zip |}} {{ :magistraleinformatica:dmi:data_notebook.zip |}} | | Setzu, Mannocci | |
| |29. | 03.12 | Py: Time Series|{{ :magistraleinformatica:dmi:timeseries.zip |}}| | Monreale, Mannocci | | |29. | 27.11 | Time series, Python Supervised Learning & Imbalanced Scenarios | {{ https://github.com/data-mining-UniPI/teaching25/blob/lectures/time%20series/Time%20series.html.pdf | Slides }}, {{ https://github.com/data-mining-UniPI/teaching25/blob/lectures/time%20series/Time%20series.html | Slides in HTML (w/ working animation) }} | | Setzu | |
| |30. | 04.12 | Responsible AI: introduction and EU Regulations | {{ :magistraleinformatica:dmi:19_rai_privacy2025.pdf | Slides}}|Monreale | | |30. | 02.12 | Shapelet-based Classification, Motif discovery | {{ :magistraleinformatica:dmi:23_time_series_motif-shapelets2023.pdf |Slides}} | {{ :magistraleinformatica:dmi:shaplet.pdf |}} {{ :magistraleinformatica:dmi:matrixprofile.pdf |}} [[https://www.cs.ucr.edu/~eamonn/MatrixProfile.html|Papers and resourse on motif]] |Monreale | |
| |31. | 09.12 | Responsible AI: privacy. | Same slides of previous lecture | {{ :magistraleinformatica:dmi:chap-anonymity.pdf |}} [[https://arxiv.org/abs/1610.05820|MIA attack against ML]]| Monreale| | |31. | 03.12 | Py: Time Series|{{ :magistraleinformatica:dmi:timeseries.zip |}}| | Monreale, Mannocci | |
| |32. | 10.12 | Responsible AI: Explaianble AI |{{ :magistraleinformatica:dmi:20_explainability_2025.pdf |XAI}}|[[https://christophm.github.io/interpretable-ml-book/|Digital book where students can find some basic XAI models and notions]] {{ :magistraleinformatica:dmi:xai-taxonomy-survey.pdf | XAI Survey describing the taxonony and dimensions of XAI}} {{ :magistraleinformatica:dmi:lore-j.pdf | LORE apaproach}}, {{ :magistraleinformatica:dmi:abele-approach.pdf |ABELE approach}}{{ :magistraleinformatica:dmi:lasts_-_explaining_any_time_series_classifier_2_.pdf |LASTS}} [[https://arxiv.org/abs/1705.07874|SHAP]][[https://arxiv.org/abs/1602.04938|LIME]]|Monreale| | |32. | 04.12 | Responsible AI: introduction and EU Regulations | {{ :magistraleinformatica:dmi:19_rai_privacy2025.pdf | Slides}}|Monreale | |
| |33. | 11.12 | XAI Python Notebook + Private and explanable FL, Assessing privacy in XAI | {{ :magistraleinformatica:dmi:xai-tutorial.ipynb.zip |XAI Notebook}} {{ :magistraleinformatica:dmi:11-dic-2025-xai.pdf | Slides}} |{{ :magistraleinformatica:dmi:glor-flex_local_to_global_rule-based_explanations_fl.pdf |GLOR-FLEX}} {{ :magistraleinformatica:dmi:fastshap-ex-pri.pdf |FASTSHAP++}} [[https://www.tdp.cat/issues21/tdp.a534a24.pdf|REVEAL]]|Naretto| | |33. | 09.12 | Responsible AI: privacy. | Same slides of previous lecture | {{ :magistraleinformatica:dmi:chap-anonymity.pdf |}} [[https://arxiv.org/abs/1610.05820|MIA attack against ML]]| Monreale| |
| |34. | 16.12 |Project Presentations - second check - ONLINE - **MANDATORY **| | |34. | 10.12 | Responsible AI: Explaianble AI |{{ :magistraleinformatica:dmi:20_explainability_2025.pdf |XAI}}|[[https://christophm.github.io/interpretable-ml-book/|Digital book where students can find some basic XAI models and notions]] {{ :magistraleinformatica:dmi:xai-taxonomy-survey.pdf | XAI Survey describing the taxonony and dimensions of XAI}} {{ :magistraleinformatica:dmi:lore-j.pdf | LORE apaproach}}, {{ :magistraleinformatica:dmi:abele-approach.pdf |ABELE approach}}{{ :magistraleinformatica:dmi:lasts_-_explaining_any_time_series_classifier_2_.pdf |LASTS}} [[https://arxiv.org/abs/1705.07874|SHAP]][[https://arxiv.org/abs/1602.04938|LIME]]|Monreale| |
| |35. | 17.12 |Project Presentations - second check - ONLINE - **MANDATORY **| | |35. | 11.12 | XAI Python Notebook + Private and explanable FL, Assessing privacy in XAI | {{ :magistraleinformatica:dmi:xai-tutorial.ipynb.zip |XAI Notebook}} {{ :magistraleinformatica:dmi:11-dic-2025-xai.pdf | Slides}} |{{ :magistraleinformatica:dmi:glor-flex_local_to_global_rule-based_explanations_fl.pdf |GLOR-FLEX}} {{ :magistraleinformatica:dmi:fastshap-ex-pri.pdf |FASTSHAP++}} [[https://www.tdp.cat/issues21/tdp.a534a24.pdf|REVEAL]]|Naretto| |
| |36. | 18.12 |Project Presentations - second check - ONLINE - **MANDATORY **| | |36. | 16.12 |Project Presentations - second check - ONLINE - **MANDATORY **| |
| | |37. | 17.12 |Project Presentations - second check - ONLINE - **MANDATORY **| |
| | |38. | 18.12 |Project Presentations - second check - ONLINE - **MANDATORY **| |
| ====== Exam ====== | ====== Exam ====== |
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