machine learning

As is obvious, data-driven solutions built or run with crappy data will not create business value, at worst, they do actual damage to business or people. Solving the issue is not hard. Problem is that too large a portion of data science sprint deliveries are measured by quantity, not by quality of deliveries. “How many … Read more

We design and implement data assets on-site and in-cloud(s) for machine learning and AI; from data extractions, transformations and loading, automated (and on-demand) data quality audits, assessment and monitoring and statistics and multivariate modeling. See more in LinkedIn