Description: The author reviews a book the debunks some of the hype we read about using quantity at the expense of quality. She also points out some unrealistic outcomes when data scientists lack business knowledge.

Description: Editorial for the May 2019 issue of Predictive Analytics & Futurism newsletter.

Description: Read the November 2020 issue of Predictive Analytics and Futurism published by the Predictive Analytics and Futurism Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: Read the August 2020 issue of Predictive Analytics and Futurism published by the Predictive Analytics and Futurism Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: This article gives a brief overview of ways to extend clustering analysis beyond basic methods such a k-means

Description: Feature article providing a brief introduction to Cython.

Description: Editorial Introduction to the issue.

Description: In this article, we will overview some popular tree-based models and understand how such models may be applied to the insurance industry.

Description: In An Introduction to Incremental Learning, by Qiang Wu and I describe how machine learning is a natural enhancement to predictive analytics through its many useful tools to derive meaning from a lot of otherwise unusable data such as handwriting. Again, there are formulas involved; but we have tried to keep them understandable to the actuary who isn’t already familiar with stochastic gradient descent, perceptrons, and principal component analysis. Incremental learning can help you refine the estimations you derive from more traditional actuarial methods.

Description: The article introduces the concept of overfitting in predictive modeling and illustrates how it hinders our ability to predict new data well.