Tuesday, 01 December 2020
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09:00 - 10:45
Data Selection, Pre-Analysis and Feature Selection (data quality, pre-treatment, missing values, feature engineering and feature selection)
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Overfitting and cross-validation
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Case study: Data Analysis and filtering
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10:45 - 11:00
Coffee Break
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11:00 - 12:30
Reminders and Q&A about supervised learning models
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12:30 - 13:30
Lunch
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13:30 - 14:30
Example: Fitting a regression tree and random forest on frequency
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Presentation: Case Study: Regression tree and random forest model adjustment for frequency and cost
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Presentatition Case study: Reminders and Q&A about supervised learning models
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14:30 - 16:00
Participants work by themselves on the case studies (individual support available thanks to Teams meeting)
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16:00 - 17:00
Correction of the case studies and closing of the day
Wednesday, 02 December 2020
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09:00 - 10:00
Interpretability of Machine learning techniques
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Case study: Features selection, partial dependence plot and Shapley Value
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Case study: Application of GBM method to highlight interactions
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10:00 - 11:00
Participants work by themselves on the case studies (individual support available thanks to Teams meeting)
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11:00 - 12:00
Correction of the case studies
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12:00 - 13:00
Lunch
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13:00 - 14:00
Reminder and example about unsupervised machine learning
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14:00 - 14:15
Break
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14:15 - 15:30
Profitability and Competition analysis (profitability and positioning assessment, reverse engineering of competitors prices)
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Example: profitability analysis with regression trees
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(Time zone: CET - Central European Time)
