9. The machine learning system, as claimed in claim 5 , wherein said synchronization manager is configured to propagate an updated prototypical model to a plurality of models comprising said model and at least one model hosted remotely from said updated prototypical model.
5. A machine learning system comprising: a computer comprising: a) an application interface component further comprising: a machine learning engine; a machine learning context; and a machine learning controller; b) a model management component further comprising; a model pool; a model pool manager; and a synchronization manager; c) an algorithm management component further comprising: an algorithm manager; an algorithm instance map; an algorithm instance map; an algorithm factory; an algorithm implementation; and an algorithm interface; wherein the machine learning engine, in combination with the machine learning context, provides said application interface component, accessible by an application program, and wherein said machine learning engine communicates a request to said algorithm management component and/or said model management component; wherein the algorithm interface defines how an algorithm instance of an algorithm implementation is accessed; wherein the algorithm manager is configured to create, retrieve, update and/or delete an algorithm instance, through said algorithm factory, and enter said algorithm instance into said algorithm instance map based on said request received through said application interface component; wherein a model is stored within said model pool and wherein a synchronization policy is associated with said model; wherein said model pool manager is configured to create, retrieve, update and/or delete said model within the model pool based on said request received through said application interface component; wherein said synchronization manager executes said synchronization policy associated with said model; wherein said machine learning controller binds an algorithm instance with said model; wherein said synchronization manager is configured to update a prototypical model only if said request contains an appropriate learning event; and wherein said appropriate learning event comprises that said model, associated with said request, and said prototypical model comprise an identical vendor, an identical algorithm structure, and a set of identical model parameter attribute types.