Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...

[DEPRECATED] Demo repository implementing an end-to-end MLOps workflow on Databricks. Project derived from dbx basic python template

Azure Databricks MLOps sample for Python based source code using MLflow without using MLflow Project.

ML Ops Accelerator: Databricks & Azure Machine Learning Unification

MLOps using Azure Databricks, Azure DevOps and Azure ML Services

MLOps practices using Azure ML service with Python SDK and Databricks for model training

Demo repository implementing an end-to-end MLOps workflow on Databricks, using Azure DevOps for CICD orchestration. Project derived from dbx basic python template

Financial Risk Assessment System

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Prescriptive guidance for building, deploying, and monitoring machine learning models with Azure Databricks using containers in line with MLOps principles and practices.

This is a repository for the LinkedIn Learning course MLOps with Databricks.

ML Ops demo for Azure Databricks and Azure ML SDK

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E2E MLOps with Databricks

End-to-end proof of concept showing core MLOps practices to develop, deploy and monitor a machine learning model for an employee retention workload using Databricks and Kubernetes on Microsoft Azure.

Code repository accompanying O'Reilly MLOps with Databricks book

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DataBricks MLOps and GenAI

Hotel Reservation Package for the MLOps with Databricks course

End-to-end demo of Databricks for MLOps, including MLflow, the registry, webhooks, scoring, feature store and auto ML

A complete end-to-end MLOps pipeline for Hotel Reservation data for the Databricks Hackathon Free Edition: https://www.databricks.com/blog/databricks-free-edition-hackathon-show-world-whats-possible-data-and-ai

Example code for integrating a custom data drift monitor into an MLOps solution using Azure Databricks and MLFlow.

This module creates and configures service principals with appropriate permissions and entitlements to run CI/CD for a project, and creates a workspace directory as a container for project-specific resources for the Databricks AWS staging and prod workspaces.

This cloud-based Crop Yield Prediction System uses Databricks, Apache Spark, and MLOps principles to forecast agricultural yields. It follows the Medallion Architecture to transform raw data into clean, analytics-ready datasets.

A simple end-to-end example of a Databricks MLOps project that uses the Iris Dataset.

This module creates and configures service principals with appropriate permissions and entitlements to run CI/CD for a project, and creates a workspace directory as a container for project-specific resources for the Azure Databricks staging and prod workspaces. It also creates the relevant Azure Active Directory (AAD) applications for the service principals.

This module sets up multi-workspace model registry between a Databricks AWS development (dev) workspace, staging workspace, and production (prod) workspace, allowing READ access from dev/staging workspaces to staging & prod model registries.

Production-grade MLOps system for hospital readmission prediction using Databricks, SageMaker, and Kubernetes

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