When it comes to exploring and applying new models and techniques, our profession is much too circumspect. But we are missing opportunities, as Artificial Intelligence is nothing without Actuarial Intelligence.
It happened again today. A client called me telling that he couldn’t open an Excel sheet he had created a couple of years before. Fortunately, LibreOffice come to his rescue and saved his day.
This post is about converting a decent plot to a good plot using a Tableau like stylesheet in matplotlib.
Principal Component Analysis (PCA) is a useful technique when you want to get a better understanding of a dataset containing a large number of correlated features. For example, in image processing, PCA is used for data compression. The main objective is to reduce the complexity of the data with a minimum loss of information.
New technologies are transforming the insurance industry. Tomorrow’s winners will be those insurers able to convert vast amounts of data into actionable insights about clients and products alike. An increasing demand for machine learning methods, combined with a growing shortage of data scientists able to create, implement and communicate these methods, call for a data pipeline that is as efficient as possible.