The acronym MLOps stands for Machine Learning Operations, which refers to the practices and tools that streamline the deployment and management of machine learning models in production. MLOps aims to bridge the gap between data science and operations, ensuring that models are effectively integrated into existing systems. This involves implementing version control, continuous integration, and monitoring, similar to traditional DevOps practices. The goal is to improve collaboration between cross-functional teams, enhance model performance, and ultimately deliver actionable insights while maintaining governance and compliance in machine learning projects.