Administrative information


Title Model Fitting and Optimization
Duration 150-180 min
Module A
Lesson Type Practical
Focus Technical - Foundations of AI
Topic Fitting and Optimization

 

Keywords


model fitting,optimization,binary classification,regression,

 

Learning Goals


 

Expected Preparation


Learning Events to be Completed Before

Obligatory for Students

Optional for Students

None.

References and background for students:

None.

Recommended for Teachers

Lesson Materials



The materials of this learning event are available under CC BY-NC-SA 4.0.

 

Instructions for Teachers


Follow the steps in the Colab.

Outline of lecture


 
Duration (min) Description Activity Material
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

 

More information

Click here for an overview of all lesson plans of the master human centred AI

Please visit the home page of the consortium HCAIM

Acknowledgements

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

 

The HCAIM consortium consists of three excellence centres, three SMEs and four Universities

HCAIM Consortium