4 Steps Tutorial: Integrating Machine Learning and DevOps for training and deploying ML code with Jenkins and Docker Containers

MLOps is the idea of combining the long-established practice of DevOps with the emerging field of Machine Learning. It is the creation of an automated environment for model development, model retraining, drift monitoring, automation of pipeline, quality control, and governance of a model into a single platform.

Any organization working with AI can automate data pipelining, model development, packaging, versioning, and monitor model accuracy. It can ease the work of data scientists and ML operations teams, enabling them to focus on higher-value creation.

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