Efficiency driven data collection and machine learning modeling recommendation

A computer-implemented method comprising:

• identifying a plurality of datasets and a plurality of machine learning (ML) modeling algorithms based on a client profile;
• assessing a cost of data collection for each dataset of the plurality of datasets;
• assessing a performance metric for each ML modeling algorithm of the plurality of ML modeling algorithms;
• and
• recommending a dataset from the plurality of datasets and an ML modeling algorithm from the plurality of ML modeling algorithms based on the assessed costs of data collection for the plurality of datasets and the assessed performance metrics for the plurality of ML modeling algorithms.

A computer program product comprising:

• one or more non-transitory computer-readable storage devices and program instructions stored on at least one of the one or more non-transitory storage devices, the program instructions executable by a processor, the program instructions comprising sets of instructions for:
• identifying a plurality of datasets and a plurality of machine learning (ML) modeling algorithms based on a client profile;
• assessing a cost of data collection for each dataset of the plurality of datasets;
• assessing a performance metric for each ML modeling algorithm of the plurality of ML modeling algorithms;
• and
• recommending a dataset from the plurality of datasets and an ML modeling algorithm from the plurality of ML modeling algorithms based on the assessed costs of data collection for the plurality of datasets and the assessed performance metrics for the plurality of ML modeling algorithms.