Actuartech

Actuartech DevOps D1 Structural Overview

A User Guide for Jupyter Notebooks

Introduction

1.1 Actuarial science in former times

1.2 Actuarial science in the technological age

1.3 Modern DevOps

2.0 Introduction

2.1 Example DevOps Requirements and Considerations

2.2 Conclusion

3.0 Introduction

3.1.1 Design

3.1.2 About Python

3.1.3 About IDEs

3.1.4 Specific IDEs

3.2.1 Main principles

3.3.1 Libraries

3.3.2 Python version

3.3.3 Environment

3.4 Git principles

3.5 Starting a project

4.0 Introduction

4.0.1 Solution Development

4.1 (a) Data Tests: Univariate/multivariate statistical tests

4.1 (b) Data Tests: Missing values

4.1 (c) Data Tests: Outlier detection

4.2 (a) Model Tests: Evaluation criteria for classification and regression

4.2 (b) Model Tests: Other criteria of importance (time, stability, continuity, interpretability, etc.)

4.2 (c) AutoML

4.3 Technical Tests: Introduction

4.3 (a) Technical Tests: Unitest example

4.3 (b) Technical Tests: Pytest example

4.4.1 Documentation: Introduction

4.4.2 Documentation: Requirements

4.4.3 Documentation: Architecture and Design

4.4.4 Documentation: Technical

4.4.5 Documentation: End User

4.4.6 Documentation: Marketing

4.5.1 API introduction

4.5.2 API Request

4.6.1 Applicative frameworks: Introduction

4.6.2 Applicative Frameworks: Popular Examples in Python

4.6.2.1 Applicative Frameworks: Dash Example