MLOps: 6-Wk Production Implementation

MLOps, or DevOps for machine learning, enables Data Science and IT teams to collaborate and increase the pace of model development and deployment via monitoring, validation, and governance of machine. With Azure ML and Azure DevOps, you can effectively and cohesively manage your datasets, experiments, models, and ML-infused applications.

We follow Agile Sprint Methodology to implement MLOps in 4 sprints which includes Testing, QA, and Productization of MLOps framework. Implementation of the entire framework takes approximately 8 weeks including the technical documentation and training.

Key Challenges solved by MLOps:

    • Model reproducibility & versioning.
    • Track, snapshot, and manage assets used to create the model.
    • Enable collaboration and sharing of ML pipelines.
    • Model auditability & explain ability.
    • Maintain asset integrity & persist access control logs.
      And many more..

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