Computing systems and methods for a unified machine learning pipeline with a logging adapter

A method for machine learning, the method executed in a computing environment comprising one or more processors, a communication interface, and memory, and the method comprising:

• a machine learning pipeline training a machine learning model in the machine learning pipeline in a development environment to generate training artifacts, and further executing the machine learning model in a production environment to generate production artifacts;
• wherein, when a training data logger and the machine learning pipeline are in communication with each other, the machine learning pipeline automatically transmits the training artifacts to the training data logger for storage in the development environment;
• and,
• wherein, when a production data logger and the machine learning pipeline are in communication with each other, the machine learning pipeline automatically transmits the production artifacts to the production data logger for storage in the production environment.

A non-transitory computer readable medium storing computer executable instructions which, when executed by at least one computer processor, cause the at least one computer processor to carry out a method for machine learning, the method comprising:

• a machine learning pipeline training a machine learning model in the machine learning pipeline in a development environment to generate training artifacts, and further executing the machine learning model in a production environment to generate production artifacts;
• wherein, when a training data logger and the machine learning pipeline are in communication with each other, the machine learning pipeline automatically transmits the training artifacts to the training data logger for storage in the development environment;
• and,
• wherein, when a production data logger and the machine learning pipeline are in communication with each other, the machine learning pipeline automatically transmits the production artifacts to the production data logger for storage in the production environment.