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 …

There are many methods for explaining why a machine learning model produces a given output in response to a given input …

We investigate the use of machine learning techniques into building statistically stable systematic allocation … estimator of the covariance matrix, or a variant of Mean Variance framework but an application of Machine Learning techniques to ….Recent advances in Neural Network, Deep Learning and Machine Learning allows a more efficient modeling of the no-linear statistical …

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 …

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 …