magistraleinformatica:dmi:start
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magistraleinformatica:dmi:start [20/11/2021 alle 01:01 (3 anni fa)] – [First Semester] Anna Monreale | magistraleinformatica:dmi:start [14/01/2022 alle 01:37 (3 anni fa)] – [Exams] Anna Monreale | ||
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|17.| 27.10 14:15-16:00 | Neural Networks | |17.| 27.10 14:15-16:00 | Neural Networks | ||
|18.| 28.10 14:15-16:00 | Python Lab on Classification | {{ : | |18.| 28.10 14:15-16:00 | Python Lab on Classification | {{ : | ||
- | |19.| 29.11 09:00-10:45 | Canceled | | | | | + | | | 29.11 09:00-10:45 | Canceled | | | | |
- | |20.| 03.11 14:15-16:00 | Python Lab on Classification + Association Rule Mining | + | |19.| 03.11 14:15-16:00 | Python Lab on Classification + Association Rule Mining |
- | |21.| 04.11 14:15-16:00 | Association Rule Mining | | | Chap.5 Association Rules: Kumar Book| | + | |20.| 04.11 14:15-16:00 | Association Rule Mining | | | Chap.5 Association Rules: Kumar Book| |
- | |22.| 05.11 09:00-10:45 | FP-Growth - Sequential Pattern Mining | {{ : | + | |21.| 05.11 09:00-10:45 | FP-Growth - Sequential Pattern Mining | {{ : |
- | |23.| 10.11 14:15-16:00 | Sequential Pattern Mining | {{ : | + | |22.| 10.11 14:15-16:00 | Sequential Pattern Mining | {{ : |
- | |24.| 11.11 14:15-16:00 | Time Series Similarities, | + | |23.| 11.11 14:15-16:00 | Time Series Similarities, |
- | |25.| 12.11 09:00-10:45 | Motif & Shapelet Discovery | {{ : | + | |24.| 12.11 09:00-10:45 | Motif & Shapelet Discovery | {{ : |
- | |24.| 17.11 14:15-16:00 | Lab: Association Rules & Sequential pattern mining by Python | {{ : | + | |25.| 17.11 14:15-16:00 | Lab: Association Rules & Sequential pattern mining by Python | {{ : |
- | |25.| 18.11 14:15-16:00 | Ethics & Privacy | {{ : | + | |26.| 18.11 14:15-16:00 | Ethics & Privacy | {{ : |
- | |26.| 19.11 09:00-10:45 | Lab: Time series | + | |27.| 19.11 09:00-10:45 | Lab: Time series | {{ : |
+ | |28.| 24.11 14:15-16:00 | Explainability | {{ : | ||
+ | |29.| 25.11 14:15-16:00 | Explainability + LAB XAI| {{ : | ||
+ | |30.| 26.11 09:00-10:45 | LAB XAI + Anomaly Detection | ||
+ | |31.| 01.12 14:15-16:00 | Anomaly Detection + Lab | | ||
+ | |32.| 02.12 14:15-16:00 | CRISP-DM | {{ : | ||
+ | |. | 03.12 09: | ||
+ | |33.| 15.12 14:15-16:00 Room C| Paper Presentation | | ||
+ | |34.| 16.12 14:15-16:00 Room C| Paper Presentation | | ||
+ | |35.| 17.12 09:00-10:45 Room C| Paper Presentation | | ||
====== Exams ====== | ====== Exams ====== | ||
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A project consists in data analyses based on the use of data mining tools. | A project consists in data analyses based on the use of data mining tools. | ||
- | The project has to be performed by a team of 2/3 students. It has to be performed by using Python. The guidelines require to address specific tasks. Results must be reported in a unique paper. The total length of this paper must be max 20 pages of text including figures. The students must deliver both: paper (single column) and well commented Python Notebooks. | + | The project has to be performed by a team of 2/3 students. It has to be performed by using Python. The guidelines require to address specific tasks. Results must be reported in a unique paper. The total length of this paper must be max 25 pages of text including figures. The students must deliver both: paper (single column) and well commented Python Notebooks. |
* First part of the project consists in the **assignments** described here: {{ : | * First part of the project consists in the **assignments** described here: {{ : | ||
- | | + | - **Dataset: |
- | * **Deadline**: | + | |
* Second part of the project consists in the assignment Task 3 described here: {{ : | * Second part of the project consists in the assignment Task 3 described here: {{ : | ||
- | | + | |
+ | |||
+ | * Third part of the project consists in the assignment Task 4 described here: {{ : | ||
+ | - Note that the document contains also rules for the delivery and final exam! | ||
+ | - Data for time series analysis: {{ : | ||
+ | | ||
+ | |||
+ | |||
+ | **Students who did not deliver the above project within 5th Jan 2022 need to ask by email a new project to the teachers. The project that will be assigned will require about 2 weeks of work and after the delivery it will be discussed during the oral exam. ** | ||
** Paper Presentation (OPTIONAL)** | ** Paper Presentation (OPTIONAL)** |
magistraleinformatica/dmi/start.txt · Ultima modifica: 19/09/2024 alle 09:58 (15 ore fa) da Mattia Setzu