Abstract: A machine learning problem assessment system that identifies potential machine learning problems in a machine learning system in which learning code evaluates data to correlate estimated learned data with data patterns. An accessing component accesses the learning code and/or the data that the learning code evaluates. A problem identifies component estimates, based on the accessed code and/or data, that there is a potential problem with machine learning system. A rectification component at least partially automatically rectifies the identified potential problem with the machine learning system by performing a computerized action on the machine learning system. The identified potential problem may affect quality (e.g., appropriateness of conclusions) and/or performance (e.g., speed) of the learning of the machine learning system.