Distributable model with biases contained within distributed data

A system for improving a distributable model with biases contained in distributed data, comprising:

• a network-connected distributable model source comprising a memory, a processor, and a plurality of programming instructions stored in the memory thereof and operable on the processor thereof, wherein the programmable instructions, when operating on the processor, cause the processor to:
• serve instances of a plurality of distributable models;
• and
• a directed computation graph module comprising a memory, a processor, and a plurality of programming instructions stored in the memory thereof and operable on the processor thereof, wherein the programmable instructions, when operating on the processor, cause the processor to:
• receive at least an instance of at least one of the distributable models from the network-connected computing system;
• operate a directed computational graph comprising a plurality of data transformation nodes;
• remove a plurality of data biases within the instance of the distributable model using at least a portion of the plurality of data transformation nodes;
• create a cleansed dataset based on the instance of the distributable model and the removed biases;
• wherein the biases comprise trends exhibited within the data;
• wherein the biases are automatically intelligently weighted and corrected by the distributed computational graph to generalize the dataset for use in a distributable model;
• train the instance of the distributable model with the cleansed dataset;
• and
• generate an update report based at least in part by updates to the instance of the distributable model.