Schedule of Risk classification and claim frequency estimation in the context of motor insurance
| Day 1, Thursday, 6 March | |
| 16:00 - 18:00 | Data Exploration and Visualization |
| Day 2, Thursday, 13 March | |
| 16:00 - 18:00 | Advanced Generalized Linear Models (GLMs) |
| Day 3, Thursday, 20 March | |
| 16:00 - 18:00 | GLM using Neural networks in Actuarial Science |
| Day 4, Wednesday, 26 March | |
| 17:30 - 19:30 | Machine Learning and Model Management |
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From 16:00 to 18:00
Data Exploration and Visualization
By PECHON Florian- Introduction to essential Python tools for analyzing and visualizing data within the context of motor insurance.
- Best practices for maintaining and sharing your work using version-controlled notebooks.
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From 16:00 to 18:00
Advanced Generalized Linear Models (GLMs)
By PECHON Florian- Deepen your understanding of GLMs by applying modern techniques to motor insurance data.
- Enhance model performance using advanced penalization methods.
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From 16:00 to 18:00
GLM using Neural networks in Actuarial Science
By PECHON Florian- Integrate neural networks with traditional models for risk modeling in motor insurance.
- Practical examples of frequency and severity modeling for claims using neural networks (no deep learning).
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From 17:30 to 19:30
Machine Learning and Model Management
By PECHON Florian- Build and optimize GBMs applied to motor liability insurance data, with performance tracking.
- Introduction to tools for model deployment and team collaboration.