Description: History of Big Data, and approaches to cope with it. The author suggests that actuaries have been using similar methods for a long time; but need to get up to speed on the newer terms and variations.

Description: Discussion about the need for, and approach to, measuring organizational expertise ton ensure the learning investment is resulting in expertise growth.

Description: Summary of the first annual predictive analytics (PA) symposium specifically targeted to help actuaries get into PA & to take it to the next level of expertise.

Description: A concise overview of Generative Adversarial Networks.

Description: The artcle looks at the most important features necessary to conduct a meaningful quantitative analysis. The article also discusses how predictive analytics should be used as a tactic to anwer question and not an end in of itself.

Description: A discussion on using the Cox Proportional Hazards Model in developing a predictive underwriting model that produces a mortality multiplier for each individual.

Description: A discussion about how many models can address the over fitting issues caused by too many variables by regularization, variable selection is still meaningful.

Description: An introduction of predictive modeling techniques that are applicable to insurance industry, including generalized linear model (GLM) and classification and regression tree model(CART). Other models such as data clustering, neural network, and support vector machine (SVM), are also briefly discussed.

Description: A discussion on how the look of charts and graphs can affect comprehension of data.

Description: This article discusses ethical issues that have arise with advancements in Data Science. Through examples of these issues address actuarial professionalism.