| Entrambe le parti precedenti la revisioneRevisione precedenteProssima revisione | Revisione precedente |
| dm:mains.santanna.dm4crm.2018 [03/05/2018 alle 14:29 (7 anni fa)] – [Calendar] Anna Monreale | dm:mains.santanna.dm4crm.2018 [09/04/2019 alle 20:47 (6 anni fa)] (versione attuale) – [Previous editions] Fosca Giannotti |
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| ^ ^ Date ^ Topic ^ Learning material ^Instructor ^ | ^ ^ Date ^ Topic ^ Learning material ^Instructor ^ |
| |01. | 15.05.2018 - 09:00-13:00 | Introduction to data mining and big data analytics | {{:dm:1.dm_ml_introduction.pdf| slides: intro}} {{:dm:2.dm_ml-casestudies.ppt.pdf| slides: case studies}} | Pedreschi | | |01. | 15.05.2018 - 09:00-13:00 | Introduction to data mining and big data analytics | {{:dm:1.dm_ml_introduction.pdf| slides: intro}} {{:dm:2.dm_ml-casestudies.ppt.pdf| slides: case studies}} | Giannotti | |
| |02. | 15.05.2018 - 14:00-18:00 | Data understanding; data preparation; Knime tutorial | {{:dm:4.dm_ml_data_preparation.pdf| slides}} {{:dm:04_dataunderstanding.pdf| slides data understanding}} {{:dm:knime_slides_mains.pdf| Tutorial Knime}} {{ :dm:01_titanic_data_understanding.zip | 01_titanic_data_understanding}} | Pedreschi, Guidotti | | |02. | 15.05.2018 - 14:00-18:00 | Data understanding; data preparation; Knime tutorial | {{:dm:4.dm_ml_data_preparation.pdf| slides}} {{:dm:04_dataunderstanding.pdf| slides data understanding}} {{:dm:knime_slides_mains.pdf| Tutorial Knime}} {{ :dm:01_titanic_data_understanding.zip | 01_titanic_data_understanding}} | Pedreschi, Guidotti | |
| |03. | 16.05.2018 - 09:00-13:00 | Clustering analysis & customer segmentation | {{:dm:dm.pedreschi.clustering.2015.pdf| slides clustering}} {{:dm:customersegmentation.pdf| slides customer segmentation}} | Pedreschi | | |03. | 16.05.2018 - 09:00-13:00 | Clustering analysis & customer segmentation | {{:dm:dm.pedreschi.clustering.2015.pdf| slides clustering}} {{:dm:customersegmentation.pdf| slides customer segmentation}} | Pedreschi | |
| |04. | 16.05.2018 - 14:00-18:00 | Clustering analysis: esercizi con Knime | {{ :dm:02_titanic_clustering.zip | 02_titanic_clustering}} | Pedreschi, Giannotti, Guidotti | | |04. | 16.05.2018 - 14:00-18:00 | Clustering analysis: esercizi con Knime | {{ :dm:02_titanic_clustering.zip | 02_titanic_clustering}} | Pedreschi, Guidotti | |
| |04. | 17.05.2018 - 14:00-18:00 | Clustering analysis: esercizi con Knime | {{ :dm:02_titanic_clustering.zip | 02_titanic_clustering}} | Pedreschi, Giannotti, Guidotti | | |05. | 17.05.2018 - 09:00-13:00 | Classification & prediction | {{:dm:dm.giannotti.pedreschi.classification.2015.pdf| slides classification}} [[http://www.r2d3.us/visual-intro-to-machine-learning-part-1/|Visual Introduction to Classification with Decision Trees]] |Pedreschi | |
| |05. | 18.05.2018 - 09:00-13:00 | Pattern and association rule mining & market basket analysis | {{:dm:3.dm-ml_patternmining.pdf|PatternMining-AR}} | Giannotti | | |06. | 17.05.2018 - 14:00-18:00 | Classification & prediction: esercizi con Knime | {{ :dm:05_titanic_classification.zip | 05_titanic_classification}} | Pedreschi, Guidotti | |
| |06. | 18.05.2018 - 14:00-18:00 | Pattern and association rule mining: esercizi con Knime |{{ :dm:03_titanic_pattern.zip | 03_titanic_pattern}} {{ :dm:04_coop_pattern.zip | 04_coop_pattern}} | Giannotti, Guidotti | | |07. | 18.05.2018 - 09:00-13:00 | Pattern and association rule mining & market basket analysis | {{ :dm:5.dm-ml_patternmining-2018.pdf |}} | Giannotti | |
| |07. | 21.05.2018 - 09:00-13:00 | Classification & prediction | {{:dm:dm.giannotti.pedreschi.classification.2015.pdf| slides classification}} [[http://www.r2d3.us/visual-intro-to-machine-learning-part-1/|Visual Introduction to Classification with Decision Trees]] | Giannotti, Pedreschi, Guidotti | | |08. | 18.05.2018 - 14:00-18:00 | Pattern and association rule mining: esercizi con Knime |{{ :dm:03_titanic_pattern.zip | 03_titanic_pattern}} {{ :dm:04_coop_pattern.zip | 04_coop_pattern}} | Giannotti, Guidotti | |
| |08. | 21.05.2018 - 14:00-18:00 | Classification & prediction: esercizi con Knime | {{ :dm:05_titanic_classification.zip | 05_titanic_classification}} | Pedreschi | | |09. | 21.05.2018 - 09:00-13:00 | More on Classification | {{ :dm:dm_ml.classification_evaluation.2017.pdf | Evaluation of classifiers }} {{ :dm:lezioneadvancedclassificationmethods1-knn_nb.pdf | KNN & Naive Bayes}} {{ :dm:lezioneadvancedclassificationmethods2-ann_svm.pdf | Neural Networks & SVM}} {{ :dm:ensemblemethod_wisdomofthecrowd.pdf | Ensemble methods & Wisdom of the crowd}} [[http://www.r2d3.us/visual-intro-to-machine-learning-part-1/|Visual Introduction to Classification with Decision Trees]] | Giannotti, Pedreschi, Guidotti | |
| |09. | 22.05.2018 - 09:00-13:00 | Social network analysis: fundamentals | {{:dm:pedreschi_sna_crash_course_mains.pptx.pdf| slides}} | Pedreschi | | |10. | 21.05.2018 - 14:00-18:00 | Prediction models for promotion performance and churn analysis | {{ :dm:5.dml-ml-exemplarproject-churn-fraude-.pdf |}}{{ :dm:5.dm_ml_exemplarprojects-shoppingbehaviour_innovators.pdf |}}| Giannotti, Guidotti | |
| |10. | 22.05.2018 - 14:00-18:00 | Prediction models for promotion performance and churn analysis | {{:dm:5.dml-ml-crm-redemption-churn-promozioni-profili-innovatori.pptx.pdf| slides}} {{:dm:crm_dm-survey.pdf|Survey of DM applications in CRM}} {{:dm:change-customer-behavior.pdf|Mining changes in customer behavior in retail marketing}} | Giannotti, Guidotti | | |11. | 22.05.2018 - 09:00-13:00 | Social network analysis: fundamentals | {{:dm:pedreschi_sna_crash_course_mains.pptx.pdf| slides}} {{ :dm:5.dml-ml-socialnetworkanalysis-.pdf |}}| Pedreschi | |
| |11. | 23.05.2018 - 09:00-13:00 | Mobility data mining & big data analytics | | Giannotti | | |12. | 22.05.2018 - 14:00-18:00 | Mobility Data Mining & Privacy |{{ :dm:mains_dm-ml-understandinghumanmobility-maggio2018.pdf }} {{ :dm:5.dml-ml-privacy_etica-.pdf |}}| Giannotti | |
| |12. | 23.05.2018 - 14:00-18:00 | Big Data Analytics: Privacy awareness | {{:dm:privacy-intro.pdf|Slides Privacy}} {{ :dm:06_class_mobility_mining.zip |}}| Giannotti, Guidotti | | |
| ===== Datasets ===== | ===== Datasets ===== |
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| **4. Classification Analysis. ** Problem: find a high-quality decision tree for predicting a feature of a customer. The report should illustrate the adopted classification methodology and the decision tree validation and interpretation, describing also the process adopted to select the proposed tree, together with its quality evaluation. | **4. Classification Analysis. ** Problem: find a high-quality decision tree for predicting a feature of a customer. The report should illustrate the adopted classification methodology and the decision tree validation and interpretation, describing also the process adopted to select the proposed tree, together with its quality evaluation. |
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| **Deadline**: send the report by email to all instructors within **23 June 2017**. Specify [MAINS] in the subject of the email. | **Deadline**: send the report by email to all instructors within **22 June 2018**. Specify [MAINS] in the subject of the email. |
| ====== Exams ====== | ====== Exams ====== |
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| ====== Previous editions ====== | ====== Previous editions ====== |
| | * [[MAINS.SANTANNA.DM4CRM.2018]] |
| * [[MAINS.SANTANNA.DM4CRM.2017]] | * [[MAINS.SANTANNA.DM4CRM.2017]] |
| * [[MAINS.SANTANNA.DM4CRM.2016]] | * [[MAINS.SANTANNA.DM4CRM.2016]] |
