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    MLOps. Software best practices for building ML solutions

    Duration
    30min
    Technologies
    AI
    Description

    Schedule

    • Achieve faster model development and experimentation.
    • Achieve faster deployment of production models.
    • Quality control.
    • Continuous integration and delivery through Azure DevOps.
    • Azure Databricks.
    • MLFlow – Machine Learning Lifecycle Platform.

    Finally, we will spend the last few minutes answering any questions that may arise during the session.

    Speaker
    Fran Pérez

    Software Development Engineer en Plain Concepts

    I work as Machine Learning Engineer in Plain Concepts, where I can combine two of my passions: machine learning and software engineering. During last five years, I’ve developed many AI solutions using Python, R … and tons of data. In recent months, I’ve been involved in the development and optimization of Machine Learning pipelines over Databricks platforms.  Previously I was an expert in Microsoft technologies, with 15 years of experience delivering desktop and web applications.