====== Data Mining (309AA) - 9 CFU A.Y. 2024/2025 ======

**Instructors:**
  * **Anna Monreale**
    * KDDLab, Università di Pisa
    * [[anna.monreale@unipi.it]]   
  * **Mattia Setzu**
    * KDDLab, Università di Pisa
    * [[mattia.setzu@unipi.it]]   

**Teaching Assistant:**
  * * **Lorenzo Mannocci**
    * University of Pisa
    * [[lorenzo.mannocci@phd.unipi.it]]  

====== News ======
  * [21.09.2024] ** Schedule updated, see details below** 
  * [14.09.2024] ** The lectures will start on 19th September 2024** 
 
====== Learning Goals ======
     * Fundamental concepts of data knowledge and discovery.
     * Data understanding
     * Data preparation
     * Clustering
     * Classification
     * Pattern Mining and Association Rules
     * Outlier Detection
     * Time Series Analysis
     * Sequential Pattern Mining
     * Ethical Issues

====== Schedule ======

**Classes**

^  Day of Week  ^  Hour  ^  Room  ^ 
|  Tuesday   |  11:00 - 13:00  |  Room C1  | 
|  Thursday  |  14:00 - 16:00  |  Room A1  | 
|  Friday    |  09:00 - 11:00  |  Room C1  | 



**Office hours - Ricevimento:**
  * Anna Monreale: TBD
  * Mattia Setzu: Infos on [[https://unimap.unipi.it/cercapersone/dettaglio.php?ri=177323&template=dett_didattica.tpl|Unimap]]

A [[https://teams.microsoft.com/l/team/19%3Aq8IK5DrzMwEE5TxVhuw4QdYEVFJ06KVITI5jSJTmaJ81%40thread.tacv2/conversations?groupId=5fae2fa6-38fd-414f-a0c9-ffbd8e6f0710&tenantId=c7456b31-a220-47f5-be52-473828670aa1|Teams Channel]] 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, but recordings of the lecture or of the previous years will be made available here for non-attending students.

====== Teaching Material ======

**Books**
^ Title ^ Authors ^ Edition ^
| [[http://www-users.cs.umn.edu/~kumar/dmbook/index.php|Introduction to Data Mining]] | Pang-Ning Tan, Michael Steinbach, Vipin Kumar | 2nd |
| [[https://link.springer.com/book/10.1007/978-3-031-48956-3|Introduction to Data Science: A Python Approach to Concepts, Techniques and Applications]] | Laura Igual,  Santi Seguí | 2nd |
| [[http://shop.oreilly.com/product/0636920034919.do| Python Data Science Handbook: Essential Tools for Working with Data]] | Jake VanderPlas | 1st |
| [[https://github.com/janishar/mit-deep-learning-book-pdf|Deep Learning]] | Ian Goodfellow, Yoshua Bengio, Aaron Courville | |
| [[https://math.mit.edu/~gs/linearalgebra/ila5/indexila5.html|Introduction to Linear Algebra]] | Gilbert Strang | 5th |


**Online tutorials**

^ ^ Authors ^
| [[https://brianmcfee.net/dstbook-site/content/intro.html|Digital Signals Theory]] | Brian McFee |
| [[https://rtavenar.github.io/blog/dtw.html|An introduction to Dynamic Time Warping]] | Romain Tavenard |
| [[https://github.com/msetzu/intro_to_ds_and_ml/blob/master/python/notebooks/Python.ipynb|Introduction to Python]] | Mattia Setzu |


**Slides**

The slides used in the course will be inserted in the calendar after each class. Some 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**

Software material available in the [[https://github.com/data-mining-UniPI/teaching23|Github repository]] (available in the coming days).

 
====== Class Calendar (2024/2025) ======

===== First Semester  =====

^ ^ Day ^ Topic ^ Teaching material ^ References ^ Video Lectures ^ Teacher ^
|    |  17.09  | Candeled   |  |   | |
|1.  |  19.09  | Overview. Introduction to KDD   | {{ :magistraleinformatica:dmi:1-overview-2024.pdf |}} {{ :magistraleinformatica:dmi:1-intro-dm-2024.pdf |}}  |Chap. 1 Kumar Book | | Monreale|
|2.  |  20.09  | Data Understanding + Data Preparation (Aggr., Sampling, Dim. Reduction, Feature Selection, Feature Creation).   |  {{ :magistraleinformatica:dmi:2-data_understanding-2024.pdf |}} {{ :magistraleinformatica:dmi:3-data_preparation-2024.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|
|3    |  24.09  | Data representation   | Slides: {{ :magistraleinformatica:dmi:Data representation.pdf |}}. References: Introduction to linear algebra (Sections 1, 3.1, 4.2, 6.1, 6.4, 6.5, 7.3), [[https://www.jmlr.org/papers/volume9/vandermaaten08a/vandermaaten08a.pdf|t-SNE paper]], [[https://arxiv.org/abs/1802.03426 | UMAP paper (Section 3)]] |  | |Setzu  |
|4.   |  26.09  | Data Cleaning + Transformations. Python Lab: Data Understanding and Preparation |{{ :magistraleinformatica:dmi:5-data_cleaning_transformation.pdf |}} | | |Monreale |

  
====== Exams ======
TBD

====== Previous years =====
[[DM-INF 2023-2024]]

[[DM-INF 2022-2023]]

[[DM-INF 2021-2022]]

[[DM-INF 2020-2021]]

[[http://didawiki.cli.di.unipi.it/doku.php/dm/dm.2019-20|DM-2019/20]]