Understand the full ML engineering lifecycle—from model building to deployment using MLOps best practices. | SCALER | Facebook

Understand the full ML engineering lifecycle—from model building to deployment using MLOps best practices. | SCALER

18 reactions · 22 shares | MLOps is a set of practices and tools for streamlining the deployment, maintenance, and management of ML models in a production environment. The goal of MLOps is to ensure that models are reliable, secure, and scalable, while also making it easier for data scientists and engineers to develop, test, and deploy ML models. Read more: https://hubs.la/Q02fGY810 #mlops #machinelearningops | Data Science Dojo | Facebook