Data driven companies effectively use regression machine learning methods for making predictions in many sectors. Cloud …-based Azure Machine Learning Studio (MLS) has a potential of expediting machine learning experiments by offering a convenient and … powerful integrated development environment. The process of evaluating machine learning models in Azure MLS has certain …

We propose a simple approach to bridge between portfolio theory and machine learning. The outcome is an out …-of-sample machine learning efficient frontier based on two assets, high risk and low risk. By rotating between the two assets, we show … important light on the appeal of machine learning into portfolio selection under estimation risk …

While payoff-based learning models are almost exclusively devised for finite action games, where players can test every … action, it is harder to design such learning processes for continuous games. We construct a stochastic learning rule …

learning process of purely and impurely altruistic agents and find that in both cases the contribution level converges towards … corresponds to findings from experiments on voluntary contribution to a public good. Crucial determinants of the learning process …

The literature on adaptive learning suggests that it can provide significant improvements to the educational process … and numerous studies have found a necessity for personalised learning, which is one of the strong suits of adaptive … learning. Adaptive learning platforms require that content be effective, and lack thereof has hindered large-scale adoption by …