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--- digitalhealth:dad_2024-2025 [08/09/2025 alle 15:40 (7 settimane fa)] – creata Anna Monreale
+++ digitalhealth:dad_2024-2025 [08/09/2025 alle 15:42 (7 settimane fa)] (versione attuale) – [Data Analytics for Digital Health (DAD)] Anna Monreale
@@ Linea 1: / Linea 1: @@
+====== Data Analytics for Digital Health (DAD) - 9 CFU A.Y. 2024/2025======
+**Instructors:**
+  * **Anna Monreale**
+    * KDDLab, Università di Pisa
+    * [[anna.monreale@unipi.it]]
+  * **Francesca Naretto**
+    * KDDLab, Università di Pisa
+    * [[francesca.naretto@unipi.it]]
+====== News ======
+====== Learning Goals ======
+     * Fundamental concepts of data knowledge and discovery.
+     * Data Types in Healthcare Data and Public Databases
+     * Data understanding
+     * Data preparation
+     * Clustering
+     * Classification
+     * Rule-based methods
+     * Outlier Detection
+     * Time Series Analysis
+     * Sequential Pattern Mining
+====== Hours and Rooms ======
+**Classes**
+^  Day of Week  ^  Hour  ^  Room  ^
+|  Monday   |   09:00 - 11:00  |  Room FIB PS4  |
+|  Tuesday|  14:00 - 16:00    |  Room C  |
+|  Friday    |  11:00 - 13:00 |  Room FIB PS4  |
+**Office hours - Ricevimento:**
+Anna Monreale: TBD - Online using Teams or in my Office (Appointment by email).
+Francesca Naretto: TBD  - Online using Teams or in my Office (Appointment by email).
+A Teams group will be used ONLY to post news, Q&A, and other stuff related to the course. The lectures will be only in presence and will **NOT** be live-streamed.
+====== Learning Material -- Materiale didattico ======
+===== Textbook -- Libro di Testo =====
+  * Pang-Ning Tan, Michael Steinbach, Vipin Kumar. **Introduction to Data Mining**. Addison Wesley, ISBN 0-321-32136-7, 2006
+    * [[http://www-users.cs.umn.edu/~kumar/dmbook/index.php]]
+    * Chapters 4,6 and 8 are also available at the publisher's Web site.
+  *  Jake VanderPlas. **[[http://shop.oreilly.com/product/0636920034919.do| Python Data Science Handbook: Essential Tools for Working with Data.]]** 1st Edition.
+  *  For Python Notions: {{ :magistraleinformatica:dmi:python_basics.ipynb.zip | Very basic notions on Python}}
+===== Slides =====
+  * The slides used in the course will be inserted in the calendar after each class. Most of them are part of the slides provided by the textbook's authors [[http://www-users.cs.umn.edu/~kumar/dmbook/index.php#item4|Slides per "Introduction to Data Mining"]].
+===== Software=====
+  * Python - Anaconda (at least 3.7 version!!!): Anaconda is the leading open data science platform powered by Python. [[https://www.anaconda.com/distribution/| Download page]] (the following libraries are already included)
+  * Scikit-learn: python library with tools for data mining and data analysis [[http://scikit-learn.org/stable/ | Documentation page]]
+  * Pandas: pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. [[http://pandas.pydata.org/ | Documentation page]]
+====== Class Calendar (2024/2025) ======
+===== First Semester  =====
+^ ^ Day ^ Topic ^ Learning material ^ References ^ Video Lectures ^ Teacher ^
+|1.  |  16.09  | Overview. Introduction to KDD  + Data Types  | {{ :digitalhealth:0-overview.pdf | Overview}} {{ :digitalhealth:1-intro-da-dm-tecs.pdf |Introduction to DADH}} {{ :digitalhealth:2-data_understanding.pdf |Data Understanding}}| Chap. 1 Kumar Book | |Monreale |
+|2.  |  18.09  | Data Understanding for tabular data   |  Slides of DU of the previous lecture  | Chap.2 Kumar Book and additioanl resource of Kumar Book: [[https://www-users.cs.umn.edu/~kumar001/dmbook/data_exploration_1st_edition.pdf|Data Exploration Chap.]] If you have the first ed. of KUMAR this is the Chap 3 | |Monreale |
+|3.  |  20.09  | Data Preparation for tabula Data    |  {{ :digitalhealth:3-data_preparation_dad.pdf |}}  | Chap.2 Kumar Book and additioanl resource of Kumar Book: [[https://www-users.cs.umn.edu/~kumar001/dmbook/data_exploration_1st_edition.pdf|Data Exploration Chap.]] If you have the first ed. of KUMAR this is the Chap 3 | |Monreale |
+|4.  |  23.09  | Data Understanding and Preparation for images | {{ :digitalhealth:4-data-understanding_images.pdf |}}|Digital Image processing, 3 edition, Rafael Gonzalez, Richard Woods | | Naretto |
+|5.  |  25.09  | Data Understanding and Preparation for images and Time Series | {{ :digitalhealth:5-data-understanding_ts.pdf |}}| | | Naretto |
+|6.  |  27.09  | Data Understanding and Preparation for Time Series + Python Lab.| {{ :digitalhealth:integrazione.zip | Intro to Python}}| | | Naretto |
+|7.  |  30.09  | Data Understanding and Preparation for Tabular Python Lab. | {{:digitalhealth:Data_Und.zip}} | | | Naretto |
+|8.  |  02.10  | Data Understanding and Preparation for Images and Time Series Python Lab. | {{:digitalhealth:Data_Und.zip}} | | | Naretto |
+|9.  |  04.10  | Data Management and Data Warehousing | {{ :digitalhealth:6-dw.pdf |}}| | | Monreale |
+|9.  |  07.10  | Data Management and Data Warehousing | {{ :digitalhealth:6-dw.pdf |}}| | | Monreale |
+|9.  |  09.10  | Data Reporting - Project presentation | {{ :digitalhealth:6-dw.pdf |}}| | | Monreale |
+|10.  |  14.10  | Clustering: intro and k-means | {{ :digitalhealth:6-basic_cluster_analysis-intro.pdf |}} {{ :digitalhealth:6-basic_cluster_analysis-kmeans.pdf |}}| Chapter 7, Introduction to Data Mining, 2nd Edition by Tan, Steinbach, Karpatne, Kumar| | Naretto |
+|11.  |  16.10  | Clustering: k-means and hierarchical| {{ :digitalhealth:7.basic_cluster_analysis-Hierarchical.pdf |}}|Chapter 7, Introduction to Data Mining, 2nd Edition by Tan, Steinbach, Karpatne, Kumar | | Naretto |
+|12.  |  21.10  | Clustering: k-means variants and density Based approaches|{{ :digitalhealth:11-basic_cluster_analysis-kmeans-variants.pdf |}} {{ :digitalhealth:10-basic_cluster_analysis-dbscan.pdf |}} |Chapter 7, Introduction to Data Mining, 2nd Edition by Tan, Steinbach, Karpatne, Kumar | | Monreale |
+|13.  |  23.10  | Clustering: Validity|{{ :digitalhealth:12-basic_cluster_analysis-validity.pdf |}} |Chapter 7, Introduction to Data Mining, 2nd Edition by Tan, Steinbach, Karpatne, Kumar | | Monreale |
+|14.  |  25.10  | Clustering and similarity for Images| {{ :digitalhealth:3.2-Clustering_images.pdf |}}| | | Naretto |
+|15.  |  28.10  | Clustering and similarity for Time Series| {{ :digitalhealth:8_time_series_similarity_2024.pdf |}}| Time Series Analysis and Its Applications. Robert H.  Shumway and David S. Stoffer. 4th edition| | Naretto |
+|16.  |  30.10  | Python Lab: Clustering| {{ :digitalhealth:clustering_diabetes.zip|}} {{ :digitalhealth:images_similarity.zip|}} {{ :digitalhealth:timeseries_similarity_clustering.zip|}} {{ :digitalhealth:clustering_tabular_tips.zip|}}| | | Naretto |
+|17.  | 04.11  | Python Lab: Clustering + Frequent Pattern Mining| {{ :digitalhealth:17_association_analysis.pdf |}}| | | Naretto, Monreale |
+|18.  | 06.11  | Frequent Pattern Mining| same slides as previous lecture| | |Monreale |
+|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| {{ :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 |}} |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| {{ :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 ======
 **Project **