Differenze

Queste sono le differenze tra la revisione selezionata e la versione attuale della pagina.

--- dm:start [18/11/2025 alle 14:50 (5 settimane fa)] – [First Semester (DM1 - Data Mining: Foundations)] Fosca Giannotti
+++ dm:start [18/12/2025 alle 11:57 (3 giorni fa)] (versione attuale) – [First Semester (DM1 - Data Mining: Foundations)] Fosca Giannotti
@@ Linea 35: / Linea 35: @@
 ====== News ======
+     * **[17.12.2025] DM Exam Registration instruction available in Exam section**.
+     * [01.12.2025] The lecture of Thursday 04/12/2025 is moved to Friday 05/12/2025 9-11 in room C (project presentation of Prof.ssa Pierotti will start at 11 after DM lecture). The last lecture will be held on Tuesday 09/12/2025 9-11 in room M1 (as Monday 08/12/2025 is holiday), while the lecture of P4DS is moved to 09/12/2025 16-18 in room C1.
+     * [19.11.2025] The lecture of Thursday 20/11/2025 will be held in room N1 due to not usability of room E.
      * [07.10.2025] The lecture of Thursday 10/10/2025 is canceled due to the UniPi Orienta event. The recovery lecture is Tuesday 14/10/2025 9-11 room M1.
      * [06.10.2025] Link to Project Groups Registration DM1 [25/26] (max 3 students for each group - access with your University of Pisa account, deadline 17/10/2025:)  [[https://docs.google.com/spreadsheets/d/1JX3VRwcZZFcTdpiguEwPsR_p4gDyRd7J89O84J7AeyY/edit?gid=0#gid=0| Link]]
@@ Linea 86: / Linea 89: @@
       * Google Meet slot - https://calendly.com/alessio-cascione-phd/30min
       * Alternative appointment by email
+      * I will be out of office from 05/12/2025 to 15/12/2025, checking emails and answering  sporadically.
@@ Linea 127: / Linea 131: @@
 Check the document:
 https://docs.google.com/document/d/1OLa02xofxRPj1zUJ7zm_boxL_ZeAFR1HWCB4lgozgz8/edit?usp=sharing
+===== Recording past years =====
+Link to past years recordings (incrementally updated with respect to the current lectures of the course)
+https://unipiit-my.sharepoint.com/:f:/g/personal/a_cascione_studenti_unipi_it/IgCdnqZe6wTKQJR_4yVrXE3gAcmqWHBSxvxW0HtsA596LWQ?e=OCa34K
 ===== Software=====
@@ Linea 153: / Linea 165: @@
 |04.| 13.10.2025 | 09-11 | E | Data Understanding | {{ :dm:01_dm1_data_understanding_2025_26.pdf | Data Understanding }} | Pedreschi |
 |05.| 14.10.2025 | 09-11 | C1 | Data Preparation | {{ :dm:02_dm1_data_preparation_2025_26.pdf | Data Preparation}}, {{ :dm:03_dm1_data_similarity_2025_26.pdf | Data Similarity}} | Guidotti |
-|04.| 16.10.2025 | 09-11 | E | Data Understanding Lab| {{ :dm:16.10.25_data_understanding_2025_lecture_in_class.zip |}} | Guidotti, Cascione |
+|06.| 16.10.2025 | 09-11 | E | Data Understanding Lab| {{ :dm:16.10.25_data_understanding_2025_lecture_in_class.zip |}} | Guidotti, Cascione |
-|06.| 20.10.2025 | 09-11 | E | Data Similarity and Introduction to Clustering | {{ :dm:03_dm1_data_similarity_2025_26.pdf | Data Similarity}}, {{ :dm:04_dm1_clustering_intro_2025_26.pdf | Introduction to Clustering}} | Guidotti |
+|07.| 20.10.2025 | 09-11 | E | Data Similarity and Introduction to Clustering | {{ :dm:03_dm1_data_similarity_2025_26.pdf | Data Similarity}}, {{ :dm:04_dm1_clustering_intro_2025_26.pdf | Introduction to Clustering}} | Guidotti |
-|07.| 23.10.2025 | 09-11 | E | Centroid-based Clustering Algorithm | {{ :dm:05_dm1_kmeans_2025_26.pdf | Centroid-based Clustering}} | Guidotti |
+|08.| 23.10.2025 | 09-11 | E | Centroid-based Clustering Algorithm | {{ :dm:05_dm1_kmeans_2025_26.pdf | Centroid-based Clustering}} | Guidotti |
-|08.| 27.10.2025 | 09-11 | E | Hierarchical Clustering Algorithm | {{ :dm:06_dm1_hierarchical_clustering_2025_26.pdf | Hierarchical Clustering}} | Guidotti |
+|09.| 27.10.2025 | 09-11 | E | Hierarchical Clustering Algorithm | {{ :dm:06_dm1_hierarchical_clustering_2025_26.pdf | Hierarchical Clustering}} | Guidotti |
-|09.| 27.10.2025 | 09-11 | E | Density-based Clustering Algorithm | {{ :dm:07_dm1_density_based_2025_26.pdf | Density-based Clustering}} | Guidotti |
+|10.| 27.10.2025 | 09-11 | E | Density-based Clustering Algorithm | {{ :dm:07_dm1_density_based_2025_26.pdf | Density-based Clustering}} | Guidotti |
-|10.|03.11.2025 | 09-11 | E | Clustering Lab | {{ :dm:03.11.25_clustering_2025_lecture_in_class.zip |}} | Pedreschi, Cascione |
+|11.|03.11.2025 | 09-11 | E | Clustering Lab | {{ :dm:03.11.25_clustering_2025_lecture_in_class.zip |}} | Pedreschi, Cascione |
-|11.|04.11.2025 | 09-11 | C1 | Classification: Overview and K-Nearest Neighbours | {{ :dm:08_dm1_classification_intro_2024_25.pptx.pdf | Classification Overview }} {{ :dm:09_dm1_knn_2024_25.pptx.pdf | KNN Classifier }} | Pedreschi |
+|12.|04.11.2025 | 09-11 | C1 | Classification: Overview and K-Nearest Neighbours | {{ :dm:08_dm1_classification_intro_2024_25.pptx.pdf | Classification Overview }} {{ :dm:09_dm1_knn_2024_25.pptx.pdf | KNN Classifier }} | Pedreschi |
-|12.|06.11.2025 | 09-11 | E | Classification: Naive Bayes Classifier and Exercises | {{ :dm:10_dm1_naive_bayes_2024_25.pptx.pdf | Naive Bayes }} | Pedreschi |
+|13.|06.11.2025 | 09-11 | E | Classification: Naive Bayes Classifier and Exercises | {{ :dm:10_dm1_naive_bayes_2024_25.pptx.pdf | Naive Bayes }} | Pedreschi |
-|13.|10.11.2025 | 09-11 | E | Classification: Evaluation | {{ :dm:11_dm1_classification_eval_2024_25.pptx.pdf | Model evaluation }} | Pedreschi |
+|14.|10.11.2025 | 09-11 | E | Classification: Evaluation | {{ :dm:11_dm1_classification_eval_2024_25.pptx.pdf | Model evaluation }} | Pedreschi |
-|14.|13.11.2025 | 09-11 | E | Classification: Decision Trees (1) | {{ :dm:12_dm1_decision_trees_2024_25.pptx.pdf | Decision trees }} | Pedreschi |
+|15.|13.11.2025 | 09-11 | E | Classification: Decision Trees (1) | {{ :dm:12_dm1_decision_trees_2024_25.pptx.pdf | Decision trees }} | Pedreschi |
-|15.|17.11.2025 | 09-11 | D5 | Classification: Decision Trees (2) |  | Pedreschi |
+|16.|17.11.2025 | 09-11 | D5 | Classification: Decision Trees (2) |  | Pedreschi |
-|16.|18.11.2025 | 09-11 | C1 | Classification: Decision Trees (2) |  | Pedreschi |
+|17.|18.11.2025 | 09-11 | C1 | Classification: Decision Trees (3) |  | Pedreschi |
+|18.|20.11.2025 | 09-11 | N1 | Classification Lab | {{ :dm:20.11.25_classification_2025_lecture_in_class.zip |}} | Guidotti, Cascione |
+|19.|24.11.2025 | 09-11 | E | Pattern Mining: Apriori | {{ :dm:14_dm1_pattern_mining_2024_25.pptx.pdf | Pattern mining & association rules }} | Pedreschi |
+|20.|25.11.2025 | 09-11 | C | Pattern Mining: Lift, Interest, Multiattribute |  | Pedreschi |
+|21.|27.11.2025 | 09-11 | E | Regression: Problem, Linear, KNN, Decision Tree | {{ :dm:13_dm1_linear_regression_2024_25.pptx.pdf | Regression }} | Pedreschi |
+|22.|01.12.2025 | 09-11 | E | Lab on Regression and Pattern Mining; FPGROWTH| {{ :dm:01.12.25_regression_2025_lecture_in_class.zip |}}, {{ :dm:01.12.25_pattern_mining_2025_lecture_in_class.zip |}}, {{ :dm:14_dm1_pattern_mining_2024_25.pptx.pdf | FPGROWTH }}| Guidotti, Cascione |
+|23.|04.12.2025 | 09-11 | C | Exercises Pattern Mining & Decision Trees |  | Guidotti |
+|24.|09.12.2025 | 09-11 | M1 | Rule-based Classifiers |{{ :dm:15_dm1_rule_based_classifier_2025_26.pdf | Rule-Based Classifier}}  | Guidotti |
 ===== Second Semester (DM2 - Data Mining: Advanced Topics and Applications) =====
@@ Linea 200: / Linea 220: @@
 - Submit the project at least 1 week before the day you selected (or within 31/12 to get +0.5 extra mark)
-===== Exam Booking Periods =====
+===== Exam Enrollment Instruction =====
-  * Exam portal link: [[https://esami.unipi.it/|here]]
+  * If you are a student of Data Science 1st year
-  * Registration Form: TBD
+  * Then register here: [[https://forms.gle/598HEN1BMQDzPmiP8|here]]
-  * 1st Appello: from TBD to TBD
+  * Else (not Data Science first year or other degrees like Digital Humanities or any other) register [[https://esami.unipi.it/|here]]
-  * 2nd Appello: from TBD to TBD
+  * Deadline: 09/01/2026
-  * 3rd Appello: from TBD to TBD
+  * Oral Exams will start from the 14/01/2026
-  * 4th Appello: from TBD to TBD
+  * The 10/01/2026 all those registered will receive an email with a link to an Agenda to select the exam day and the time slot
-  * 5th Appello: from TBD to TBD
-  * 6th Appello: from TBD to TBD