Productionizing ML Models with Proper Data - Gestalt IT

As enterprises are starting to engage machine learning models and embed them into heavy-duty production systems, they face a lot of hurdles. Especially, MLOps lacks enterprise-grade feature stores to stores, search, replace, and collaborate on ML models. This article will explore that problem in detail, and explore one such solution offered by Tecton.ai. Until about 15 years or so ago, we had a software development/deployment problem – releasing a new software version, collecting feedback, identifying new features, and gathering changed customer requirements were all too slow. It took a long time to get the feedback and close the loop in developing new versions – sometimes months or even longer.