Title | Model Fitting and Optimization | ![]() |
Duration | 150-180 min | |
Module | A | |
Lesson Type | Practical | |
Focus | Technical - Foundations of AI | |
Topic | Fitting and Optimization |
model fitting,optimization,binary classification,regression,
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The materials of this learning event are available under CC BY-NC-SA 4.0.
Follow the steps in the Colab.
Duration (min) | Description | Activity | Material |
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0-15 min | A brief overview of the tasks and learning goals | Instructions by the lecturer | colab practical link for lecturer |
15 - 40 min | Task 1 - Explore the dataset - Visualise and summarise the findings. Normalize and label the target variable. | Reporting - investigation of data (bias, redundancy, ethical) | |
40 - 75 min | Task 2 - Model Evaluation - Model Evaluation based on Train and Test data. | Coding | |
75 - 105 min | Task 3 - Model Optimization - Use hyperparameter tuning and modify the threshold to improve the performance. | Coding | |
105 - 135 min | Task 4 - Model Optimization - Summarise the model performance of Task 3 | Reporting - Summary | |
135-150 min | Summary of the practical | Conclusion by the lecturer |
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 |