Abstract: A system and method for facilitating interoperability of data transformations developed in different programming platforms under a unified platform including receiving a first transformation utilizing a first programming platform; receiving information about the first transformation; wrapping the first transformation; including the wrapped, first transformation in a transformation pipeline, the transformation pipeline including a second transformation that is wrapped, the second transformation utilizing a second programming platform different from the first programming platform; and executing the transformation pipeline including the wrapped, first transformation and the wrapped, second transformation in batch mode or real-time streaming mode.

Abstract: A system and method for generating a recommendation system based on supervised learning includes generating a master dataset, selecting a subset of features and a subset of rows in the master dataset, selecting a supervised learning method, building a first model based on a first dataset and the supervised learning method, the first dataset being restricted to the subset of features and the subset of rows in the master dataset, determining a set of candidate items, identifying a first user, generating a prediction of a user response of the first user to the set of candidate items based on the first model, and generating a recommendation of a first candidate item based on the prediction.

Abstract: A system and method for providing various user interfaces is disclosed. In one embodiment, the various user interfaces include a series of user interfaces that guide a user through the machine learning process. In one embodiment, the various user interfaces are associated with a unified, project-based data scientist workspace to visually prepare, build, deploy, visualize and manage models, their results and datasets.