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Accelerating MLOps Using Databricks and Vertex AI on GCP

Overview

Google Cloud and Databricks launched their partnership in 2021, enabling organizations to use Databricks to create a lakehouse for data engineering, data science, machine learning, and analytics on GCP. For data science and ML engineering teams, key MLOps capabilities can be unlocked by combining the power of Databricks’ Spark and managed MLFlow framework with Vertex AI’s simple, autoscaling, and secure model deployment environment.

Vertex AI predictions offers a service to deploy models trained in any framework for online or batch prediction use cases, simplifying the serving process by offering managed ML accelerators, automated model monitoring and explainability.

In this session, attendees will learn how to serve real-time prediction models built and trained on Databricks using Vertex AI. We will highlight the business benefits realized by implementing MLOps on an open source platform: accelerating the model development and deployment lifecycle while decreasing the time to make data-driven business decisions.

Type

  • Session

Format

  • Virtual

Track

  • Data Science, Machine Learning and MLOps

Difficulty

  • Advanced

Duration

  • 0 min

Session Speakers

Headshot of Ivan Nardini

Ivan Nardini

Customer Engineer, Smart Analytics

Google Cloud

Headshot of Deb Lee

Deb Lee

Customer Engineer, Smart Analytics

Google Cloud

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