KMDS (Knowledge Management for Data Science) is a machine learning reproducibility framework designed to bring repeatability, methodology, and business impact to ML projects. It helps mid-market tech companies and consulting teams reduce chaos and improve confidence in offline and batch ML workflows.
For dataset-specific examples and real-world workflows (SBA, Olist, ITSM), please refer to the main repository README.
Keywords: reproducible ML, KMDS toolkit, ML consulting, reproducibility in machine learning, mid-market ML solutions, reproducibility framework.