Complete Guide to MLOps - Machine Learning Essentials

This 41-minute video from Kode Kloud provides a comprehensive guide to MLOps, revealing how leading tech companies automate, scale, and deploy machine learning models. Discover the essential blueprint for mastering CI/CD pipelines, real-time monitoring, and infrastructure automation in machine learning operations. Learn how MLOps makes machine learning scalable, the DevOps skills needed to become an MLOps Engineer, and the best tools like MLflow, Kubeflow, and Airflow. The content covers the complete MLOps lifecycle, including the differences between DevOps and MLOps, continuous integration, deployment, training, and monitoring in MLOps environments. Explore MLOps architecture and understand the specific roles and responsibilities of MLOps engineers who bridge the gap between data science and production deployment.