Corso di Laurea Magistrale in |
Data Mining (6 CFU - 48 ore)|
(a) application of data mining techniques learned in the course to
the analysis of some real-world dataset or to the
development of efficient big-data processing tools;
and (b) practical experience with Spark
Groups: the project is carried out by groups of at most 5 students (ideally, 4-5 students per group). We call early groups, those groups who complete the project by the end of the course, presenting it to the class during the last 2-3 lectures, and late groups the others.
Types of projects:
Deadlines for early groups:
Deadlines for late groups:
Structure of the report/presentation: The report and, for early groups, the presentation, (either in Italian or in English) should be structured as follows:
TITLE. Title of the project, and names+student ID of the group members. For suggested projects use the title "Suggested Project Goal A/B", for free projects come up with a meaningful title
1. DATASET and OBJECTIVEs. Describe the dataset and the *specific objectives* pursued in the project. For free projects, some information about the context which the data refer to may be useful.
2. DESCRIPTION of the ACTUAL WORK DONE. Describe the various steps performed during the project.
3. RESULTs. Summarize the main results of the analysis. Here, some tables and graphs are much helpful
4. CONCLUSIONs (optional). Write any final remarks and comments you have.
Groups can adapt the above structure as they wish, as long as they do not exceed 7 pages (using a "human readable" font size), for the report, and 12 slides for the 10-min presentation.
Evaluation: The evaluation of the project (25% of the final grade) will be based on: report, presentation (in class or at the oral exam), rigorousness of methodology, effectiveness/performance. Early groups who present their work at the end of the course will receive 1 extra point added to the final grade
|Ultimo aggiornamento: 22 maggio 2017||Vai alla pagina iniziale|