Description: Alternative sources of learning available for free or at low cost if you wish to round out your F&F education about machine learning, artificial neural networks, genetic algorithms and the millennia of biological advances we draw from when we use these techniques.

Description: Continuation of a tutorial on Fuzzy (vs. Boolean, or 'crisp') logic and how you can use it to create actuarial models that better fit the real world. The article provides basic theory in non-technical terms and shows applications using the R programming language.

Description: Summary of the issue, with emphasis on common sense and accuracy rather than blind precision. Also describes two F&F contests.

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: Neural Networks are no longer limited to classification and regression solutions to numeric problems. CNNs add the ability to classify images, and GANs can create new images. Learn how these capabilities can provide competitive advantages to early adopters, how they work, and how to implement them.

Description: This abstract describes a presentation that introduces new methods such as Experimental Mathematics, Genetic Algorithms, Predictive Modeling, Deterministic Chaos, Fractal Geometry, Behavioral Economics, Cellular Automata and other topics in Complexity Sciences.

Description: The PA Symposium will be an immersive experience benefiting entry level actuaries through senior managers, and PA newbies through advanced practitioners.

Description: Editorial for the December 2019 print edition of Predictive Analytics & Futurism newsletter describing the large number of informational resources available to PAF Section members.

Description: Provides a simplified explanation of the modeling and statistical terms currently in use by the profession, and provides a list of publications worth reading in regards to complexity science plus a list of free software.

Description: A review of the book Abundance by Steven Kotler and Peter H. Diamandis.