Differenze

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

--- digitalhealth:0001a [29/11/2024 alle 17:40 (4 mesi fa)] – [Exams] Anna Monreale
+++ digitalhealth:0001a [11/02/2025 alle 09:25 (7 settimane fa)] (versione attuale) – [First Semester] Anna Monreale
@@ Linea 91: / Linea 91: @@
 |19.  | 08.11  | Sequential Pattern Mining| {{ :digitalhealth:18_sequential_patterns_2024.pdf |}}| | |Monreale |
 |20.  | 11.11  | Python lab: FPM + SPM|{{ :digitalhealth:AR_SPM.zip |}} | | |Naretto |
-|21.  | 13.11  | Classification for tabular| | | |Naretto |
+|21.  | 13.11  | Classification for tabular| {{ :digitalhealth:classification-dt-2023.pdf |}}| | |Naretto |
 |22.  | 15.11  | Classification for tabular|{{ :digitalhealth:10-KNN.pdf |}} | | |Naretto |
-|23.  | 18.11  | Classification for tabular|{{ :digitalhealth:10-lg.pdf |}} | | |Naretto |
+|23.  | 18.11  | Classification for tabular|{{ :digitalhealth:10-lg.pdf |}} |https://web.stanford.edu/~jurafsky/slp3/5.pdf | |Naretto |
 |24.  | 20.11  | Project| | | |Monreale, Naretto |
 |25.  | 22.11  | Classification for tabular|{{ :digitalhealth:10-Rule-Based-Classifiers.pdf |}} {{ :digitalhealth:11_2021-naive_bayes.pdf|}}| | |Naretto |
 |26.  | 25.11  | Classification for tabular|{{ :digitalhealth:13_ensemble_2023.pdf |}}| | |Naretto |
-|27.  | 27.11  | Python Lab: Classification & Project Work| | ||Naretto |
+|27.  | 27.11  | Python Lab: Classification & Project Work| {{ :digitalhealth:Classification-diabetes.ipynb.zip}}| ||Naretto |
 |28.  | 29.11  | Time seres classification via shapelet and Motif Discovery| {{ :digitalhealth:23_time_series_motif-2024.pdf |Shapelets & Motifs}}| {{ :digitalhealth:shaplets.pdf |}}{{ :digitalhealth:matrixprofile.pdf |}}| |Monreale |
+|29.  | 2.12  | Regression and Imbalanced classification|{{ :digitalhealth:16_linear_regression_2020.pdf}} {{ :digitalhealth:imbalanced-learning.pdf |}}{{ :digitalhealth:imbalanced-classification.zip |}}| |Naretto |
+|30.  | 4.12  | Outliers and anomalies detection: tabular| {{ :digitalhealth:21_anomaly_detection_2020.pdf |}}| |Naretto |
+|31.  | 6.12  | Outliers and anomalies detection: time series| {{ :digitalhealth:AnomalyDetection-1.ipynb.zip|}}| |Naretto |
+|32.  | 9.12  | Forecasting of time series| {{ :digitalhealth:ts_forecasting.pdf|}}| |Naretto |
 ====== Exams ======
@@ Linea 108: / Linea 112: @@
 * First part of the project consists in the **assignments** described here: {{ :digitalhealth:data_analytics_for_digital_health_project_du_cl.pdf |Project Description: DU and Clustering}}
   - **Dataset**: Please download it from Teams
-  - **Deadline**: the fist part has to be delivered by ** December 2th, 2024 **. The delivery will be through Teams' assignement
+  - **Deadline**: the fist part has to be delivered by ** December 2th, 2024 **. The delivery will be through Google Drive folders (write to Francesca Naretto for the creation of your group folder).
+* Second part of the project: the document is in Teams.
+ - **Deadline**: January 5th, 2025
+**Students who did not deliver the above project within **January 5th, 2025** need to ask by email a new project to the teachers. The project that will be assigned will require about 20 days of work and after the delivery it will be discussed during the oral exam. **
-**Students who did not deliver the above project within **Dec 31, 2024** need to ask by email a new project to the teachers. The project that will be assigned will require about 20 days of work and after the delivery it will be discussed during the oral exam. **