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    Many-Model Machine Learning for Enterprises

    Duration: 60 minutes Host: Taylor van Valkenburg, Data Science Expert/Senior Consultant,
    DS & AI Practice Team     This session is offered as a scheduled group session with our expert.
    Ask for available time slots
    Blog Cover - Whats New With GPT-4 - Features and Limitations
    Blog Cover Featured - Whats New With GPT-4 - Features and Limitations

    What To Expect

    This presentation focuses on our experience designing and building a flexible, easy-to-use, and production-ready framework for many-model machine learning.

    An Overview of Azure Machine Learning (ML)

    MLOps Best Practices on Azure ML

    Azure Databricks

    Azure ML and Databricks Integration

    Take a crash course on the Azure ML platform and learn how it helps in developing and managing machine learning models.

    See how we implemented MLOps best practices on the Azure ML platform to deliver a foundation for many-model machine learning solutions that scaled to over 70,000 models.

    Learn about Azure Databricks and how it helps in running and deploying interactive, scheduled, and real-time data analysis workloads in collaborative environments.

    Learn how to use the integration to scale easily with Spark while using a unified code base.

    An Overview of Azure Machine Learning (ML)

    MLOps Best Practices on Azure ML

    Take a crash course on the Azure ML platform and learn how it helps in developing and managing machine learning models.

    See how we implemented MLOps best practices on the Azure ML platform to deliver a foundation for many-model machine learning solutions that scaled to over 70,000 models.

    Azure Databricks

    Azure ML and Databricks Integration

    Learn about Azure Databricks and how it helps in running and deploying interactive, scheduled, and real-time data analysis workloads in collaborative environments.

    Learn how to use the integration to scale easily with Spark while using a unified code base.

    An Overview of Azure Machine Learning (ML)

    Take a crash course on the Azure ML platform and learn how it helps in developing and managing machine learning models.

    MLOps Best Practices on Azure ML

    See how we implemented MLOps best practices on the Azure ML platform to deliver a foundation for many-model machine learning solutions that scaled to over 70,000 models.

    Azure Databricks

    Learn about Azure Databricks and how it helps in running and deploying interactive, scheduled, and real-time data analysis workloads in collaborative environments.

    Azure ML and Databricks Integration

    Learn how to use the integration to scale easily with Spark while using a unified code base.

    Valkenburg
    Valkenburg

    About Our Speaker

    Taylor van Valkenburg is a data scientist with Lingaro’s data science and AI practice. He has extensive experience delivering advanced analytics in a variety of sectors, such as human resources, procurement, and consulting. Taylor is passionate about using best practices in AI engineering alongside cutting-edge advancements in data science to build solutions that make an impact for businesses. Taylor speaks about topics related to data science and AI engineering and has a special interest in the intersection between emerging technologies and public policy. 

    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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