Systems and methods for universal machine learning pipeline execution

An apparatus for automated model development, the apparatus comprising:

• configuration circuitry configured to parse a configuration file;
• an execution engine configured to:
• generate, based on the parsed configuration file, model code for training and testing a machine learning model;
• generate a machine learning pipeline, wherein the machine learning pipeline comprises the model code and a data processing engine;
• a monitoring driver configured to instantiate a monitoring engine to monitor the machine learning pipeline,
• wherein the execution engine is further configured to cause execution of the machine learning pipeline,
• wherein the monitoring engine is further configured to, during execution of the machine learning pipeline, generate model performance data;
• and
• communications hardware configured to receive, from the execution engine, model output data, wherein the model output data comprises a trained model and model performance data.

An apparatus for automated model development, the apparatus comprising:

• means for parsing a configuration file;
• means for generating, based on the parsed configuration file, model code for training and testing a machine learning model;
• means for generating a machine learning pipeline, wherein the machine learning pipeline comprises the model code and a data processing engine;
• means for instantiating a monitoring engine to monitor the machine learning pipeline;
• means for causing execution of the machine learning pipeline;
• means for, during execution of the machine learning pipeline, generating model performance data;
• and
• means for receiving model output data, wherein the model output data comprises a trained model and model performance data.