The introductory portion of this talk will review some state-of-the-art machine learning techniques. We will discuss concepts of ensembles and popular methodologies within this category. We’ll touch upon collaborative filtering techniques used for recommendation systems, and we’ll present certain algorithms published specifically for healthcare models. 

We will later focus on application of the mentioned machine learning techniques covering healthcare, recommendation systems and portfolio construction in finance. We will refer to some past data modeling competitions such as Netflix (2007) and the Heritage Health Prize (2014) where thousands of algorithms were pitted against each other and evaluated impartially on a withheld data set. Within the financial application we will present risk management models that can be used to dictate/constrain positions within the portfolio construction process.