Description: A review of the Johns Hopkins Data Science Specialization courses with special emphasis on how they may be useful to actuaries.

Description: An autobiographical journey from actuarial student to data scientist.

Description: The Possible Role of Convolutional Neural Networks in Mortality Risk Protection

Description: Read the June issue of Predictive Analytics & Futurism published by the Predictive Analytics & Futurism Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: Machine learning models are not black-boxes; these models can easily be interpreted using tools like SHAP, LIME and Anchor. These tools can facilitate the understanding of the model and the business problem. We can used these tools to build better models and communicate how predictions are generated. This article demonstrates their use in a mortality model.

Description: In Complexity: A Guided Tour, readers are given a short history lesson on the roots of dynamical systems theory, chaos and prediction.

Description: Discusses the three complexity science sessions at the Annual Meeting that were sponsored by the Section.

Description: The Delphi Method is discussed in detail. The method attempts to filter out the consensus bias that can result from societal forces by employing a technique whereby an anonymous collection of opinions is used, supplemented by feedback loops that can be used to influence outcomes.

Description: This article provides a brief introduction to forecasting methods that are potentially relevant to actuarial work.

Description: The author reviews the book, The Perfect Swarm: The Science of Complexity in Everyday Life, by Len Fisher. He provides his own interpretation of the power of the swarm and touts the book as a straightforward and informative introduction to various aspects of complexity science.