In today's data-driven world, organizations are increasingly leveraging the power of machine learning (ML) to gain insights, automate tasks, and make informed decisions. However, the journey from creating an effective ML model to deploying it in production and realizing its full potential can be fraught with challenges. This is where MLOps , a specialized practice built upon the foundation of DevOps , comes into play. While both approaches share common goals, their specific focus areas and implementation strategies differ significantly. Understanding DevOps: The Foundation for Efficiency DevOps is a set of cultural practices and tools that aim to bridge the gap between development, operations, and security teams. This collaboration fosters continuous integration and continuous delivery (CI/CD) , meaning code changes are frequently integrated and automatically tested, deployed, and monitored. DevOps has revolutionized software d...
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