| Title | Unsupervised Learning | |
| Duration | 60 mins | |
| Module | A | |
| Lesson Type | Practical | |
| Focus | Practical - AI Modelling | |
| Topic | Data analysis |
Clustering, Ethics, Data normalization,
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The materials of this learning event are available under CC BY-NC-SA 4.0.
This learning event consist of laboratory tasks that shall be solved by the students with the help of the leading instructor.
You can base this class around the notebooks.
| Duration (min) | Description | Concepts | Activity | Material | |
|---|---|---|---|---|---|
| 5 | Dataset | Tesco loyalty program DB, customers, dates, spend, days of week | Practice | Data: DataSet_Tesco5000_withDaynum.csv | |
| 15 | Clustering in 2D | Observations with raw data, Kmeans with 2, 3, 4 clusters | Notebook, coding | Notebook: 03_Clustering_I | |
| 10 | Clustering in 2D | effect of data normalization (MinMax / StandardScaler), Kmeans with 2, 3, ... 25 clusters | Notebook, coding | Notebook: 03_Clustering_I | |
| 5 | Cluster centers | plot custer centers: raw vs normalized data | Notebook, coding | Notebook: 03_Clustering_I | |
| 5 | Clustering depending on day of week | plot dependence of spending vs day-of-week (Mon, Tue, ...Sun) | Notebook, coding | Notebook: 03_Clustering_I | |
| 10 | Clustering depending on monthly visit | plot which months do the customers prefer. effect of cluster size. observations of extreme customers | Notebook, coding | Notebook: 03_Clustering_I | |
| 10 | Clustering: relate to ethics | relation to ethical datasets | ? | ? |
Click here for an overview of all lesson plans of the master human centred AI
Please visit the home page of the consortium HCAIM
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The Human-Centered AI Masters programme was co-financed by the Connecting Europe Facility of the European Union Under Grant №CEF-TC-2020-1 Digital Skills 2020-EU-IA-0068. The materials of this learning event are available under CC BY-NC-SA 4.0
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The HCAIM consortium consists of three excellence centres, three SMEs and four Universities
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