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dm:mains.santanna.dm4crm.2018 [03/05/2018 alle 14:29 (4 anni fa)]
Anna Monreale [Calendar]
dm:mains.santanna.dm4crm.2018 [09/04/2019 alle 20:47 (3 anni fa)] (versione attuale)
Fosca Giannotti [Previous editions]
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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 & predictionesercizi 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.
  
-**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]]
dm/mains.santanna.dm4crm.2018.1525357779.txt.gz · Ultima modifica: 03/05/2018 alle 14:29 (4 anni fa) da Anna Monreale