Differenze

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

--- digitalhealth:0001a2025 [08/09/2025 alle 14:28 (3 giorni fa)] – [Hours and Rooms] Anna Monreale
+++ digitalhealth:0001a2025 [08/09/2025 alle 14:45 (3 giorni fa)] (versione attuale) – [Hours and Rooms] Anna Monreale
@@ Linea 1: / Linea 1: @@
-====== Data Analytics for Digital Health (DAD) 2025-2026 ======
-**Instructors:**
-  * **Anna Monreale**
-    * KDDLab, Università di Pisa
-    * [[anna.monreale@unipi.it]]
-  * **Francesca Naretto**
-    * KDDLab, Università di Pisa
-    * [[francesca.naretto@unipi.it]]
-====== 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 ======
-====== 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 nor registered.
-====== 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]]