AI Tools for Actuaries (work in progress)
About This Project
This project aims to empower the actuarial profession with modern machine learning and AI tools. We provide comprehensive teaching materials that consist of lecture notes (technical document) building the theoretical foundation of this initiative. Each chapter of these lecture notes is supported by notebooks and slides which give teaching material, practical guidance and applied examples. Moreover, hands-on exercises in both R and Python are provided in additional notebooks.
Lecture Notes (Technical Document)
Notebooks, Slides and Code
- Chapter 1: Introduction and Preliminaries
- Chapter 2: Regression Models
- Chapter 3: Generalized Linear Models
- Chapter 4: Interlude
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Chapter 5: Feed-Forward Neural Networks
The Theory of FNNs
FNN One-Hot Encoding Example
FNN Embedding Example
CANN Example
LocalGLMnet Example
- Chapter 6: Regression Trees and Random Forests