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dm:mains.santanna.dm4crm.2019 [09/04/2019 alle 22:00 (5 anni fa)]
Fosca Giannotti [Calendar]
dm:mains.santanna.dm4crm.2019 [11/04/2019 alle 14:17 (5 anni fa)]
Anna Monreale [Datasets]
Linea 51: Linea 51:
 |06.   | Lun 15.04.2019 - 14:00-18:00  | Classification & prediction: exercises with Knime | {{ :dm:05_titanic_classification.zip | 05_titanic_classification}} | Pedreschi, Rossetti | |06.   | Lun 15.04.2019 - 14:00-18:00  | Classification & prediction: exercises with Knime | {{ :dm:05_titanic_classification.zip | 05_titanic_classification}} | Pedreschi, Rossetti |
 |07.   | Mar 16.04.2019 - 09:00-13:00  | More on Classification: from decision trees to deep learning | {{ :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}}  | Pedreschi | |07.   | Mar 16.04.2019 - 09:00-13:00  | More on Classification: from decision trees to deep learning | {{ :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}}  | Pedreschi |
-|08.   | Mar 16.04.2019 - 14:00-18:00  | Classification & prediction: exercises with Knime |  | Giannotti, Rossetti |+|08.   | Mar 16.04.2019 - 14:00-18:00  | Classification & prediction: exercises with Knime. Project work |  | Giannotti, Rossetti |
 |09.   | Mer 17.04.2019 - 09:00-13:00  | Pattern and association rule mining & market basket analysis | {{ :dm:5.dm-ml_patternmining-2018.pdf |}} | Giannotti | |09.   | Mer 17.04.2019 - 09:00-13:00  | Pattern and association rule mining & market basket analysis | {{ :dm:5.dm-ml_patternmining-2018.pdf |}} | Giannotti |
 |10.   | Mer 17.04.2019 - 14:00-18:00  | Pattern and association rule mining: exercises with Knime |{{:dm:03_titanic_pattern.zip | 03_titanic_pattern}} {{ :dm:04_coop_pattern.zip | 04_coop_pattern}}  | Giannotti, Rossetti | |10.   | Mer 17.04.2019 - 14:00-18:00  | Pattern and association rule mining: exercises with Knime |{{:dm:03_titanic_pattern.zip | 03_titanic_pattern}} {{ :dm:04_coop_pattern.zip | 04_coop_pattern}}  | Giannotti, Rossetti |
 |11.   | Gio 18.04.2019 - 09:00-13:00  | Case studies. 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 | |11.   | Gio 18.04.2019 - 09:00-13:00  | Case studies. 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 |
-|12.   | Gio 18.04.2019 - 14:00-18:00  | Data Science Privacy & Ethics | {{ :dm:5.dml-ml-privacy_etica-.pdf |}}| Giannotti |+|12.   | Gio 18.04.2019 - 14:00-18:00 Hints on data science with Python. Data Science Privacy & Ethics| {{ :dm:5.dml-ml-privacy_etica-.pdf |}}| Giannotti, Rossetti |
 ===== Datasets ===== ===== Datasets =====
  
Linea 61: Linea 61:
 0. {{ :dm:data.txt.zip | Iris}}. (for details see [[https://archive.ics.uci.edu/ml/datasets/iris]]) 0. {{ :dm:data.txt.zip | Iris}}. (for details see [[https://archive.ics.uci.edu/ml/datasets/iris]])
  
-1. {{ :dm:human_resources.csv.zip | Human Resources}}. (for details see [[https://www.kaggle.com/ludobenistant/hr-analytics]])+1. {{ :dm:titanic_train.csv.zip | Titanic}}. (for details see [[https://www.kaggle.com/c/titanic]])
  
-2. {{ :dm:telco_churn.csv.zip | Telco Churn}}. (for details see [[http://didawiki.di.unipi.it/doku.php/dm/mains.santanna.dm4crm.2016]])+2. {{ :dm:human_resources.csv.zip | Human Resources}}. (for details see [[https://www.kaggle.com/ludobenistant/hr-analytics]]) 
 + 
 +3. {{ :dm:telco_churn.csv.zip | Telco Churn}}. (for details see [[http://didawiki.di.unipi.it/doku.php/dm/mains.santanna.dm4crm.2016]]) 
 + 
 +4. {{ :dm:adult.csv.zip | Adult}}. (for details see [[https://archive.ics.uci.edu/ml/datasets/Adult]]) 
 + 
 +5. {{ :dm:credit_card.txt.zip | Credit Card}} (for details see [[https://archive.ics.uci.edu/ml/datasets/default+of+credit+card+clients]])
  
-3. {{ :dm:adult.csv.zip | Adult}}. (for details see [[https://archive.ics.uci.edu/ml/datasets/Adult]]) 
  
-4. {{ :dm:titanic_train.csv.zip | Titanic}}. (for details see [[https://www.kaggle.com/c/titanic]]) 
  
 ===== Exercises ===== ===== Exercises =====
dm/mains.santanna.dm4crm.2019.txt · Ultima modifica: 17/04/2019 alle 21:57 (5 anni fa) da Fosca Giannotti