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    Introduction to MLflow on Azure Databricks

    Duration: 60 minutes Hosts: Ernest Kuśmierz, AI and ML Engineer/Lead Consultant,
    DS and AI Practice Team     This session is offered as a scheduled group session with our expert.
    Ask for available time slots
    Introduction to MLflow on Azure Databricks-1
    Introduction to MLflow on Azure Databricks-2

    What to expect

    In this session, you’ll learn more about MLflow, the open-source platform for the complete management of machine learning life cycle.

    Tracking

    Models and Projects

    Model Registry

    Model Serving

    Learn how to track machine learning training runs using MLflow.

    Find out what an MLflow model is, the different models that MLflow supports, and how to run an MLflow project on Databricks.

    Learn how MLflow Model Registry is used to manage the full life cycle of an MLflow model.

    Learn how to make an MLflow model accessible to a large user base.

    Tracking

    Models and Projects

    Learn how to track machine learning training runs using MLflow.

    Find out what an MLflow model is, the different models that MLflow supports, and how to run an MLflow project on Databricks.

    Model Registry

    Model Serving

    Learn how MLflow Model Registry is used to manage the full life cycle of an MLflow model.

    Learn how to make an MLflow model accessible to a large user base.

    Tracking

    Learn how to track machine learning training runs using MLflow.

    Models and Projects

    Find out what an MLflow model is, the different models that MLflow supports, and how to run an MLflow project on Databricks.

    Model Registry

    Learn how MLflow Model Registry is used to manage the full life cycle of an MLflow model.

    Model Serving

    Learn how to make an MLflow model accessible to a large user base.

    Ernest Kusmierz, circle
    Ernest Kusmierz, circle

    About Our Speaker

    Ernest Kuśmierz is an accomplished professional with a wealth of expertise in various areas, including DevOps, infrastructure, cloud, and MLOps. With a strong background in these domains, Ernest is highly skilled in the responsible and efficient operationalization of machine learning projects.

    Ask for available time slots

    Fill in and submit this form to signify your interest. Within two days of registering, a representative will reach out to you to discuss your team’s knowledge needs and provide available time slots for you to choose from.
     

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