What You Need to Know Before
You Start

Starts 3 June 2025 06:07

Ends 3 June 2025

00 days
00 hours
00 minutes
00 seconds
course image

Using MLflow and Databricks to Deploy ML Models in Production

Explore MLflow and Databricks for production ML model deployment. Learn end-to-end management, model tracking, and deployment strategies, plus Databricks' Feature Store and AutoML.
Data Science Festival via YouTube

Data Science Festival

2408 Courses


58 minutes

Optional upgrade avallable

Not Specified

Progress at your own speed

Free Video

Optional upgrade avallable

Overview

Explore MLflow and Databricks for production ML model deployment. Learn end-to-end management, model tracking, and deployment strategies, plus Databricks' Feature Store and AutoML.

Syllabus

  • **Introduction to MLflow and Databricks**
  • Overview of MLflow
    Introduction to Databricks platform
    Understanding the Production ML Workflow
  • **MLflow for Model Management**
  • Installing and Setting up MLflow
    Tracking Experiments and Runs
    Managing ML Models with MLflow Registry
  • **Model Deployment Strategies**
  • Batch vs. Real-Time Deployment
    Deploying Models with MLflow
    Managing Model Versions and Rollbacks
  • **Integrating Databricks with MLflow**
  • Configuring MLflow with Databricks
    Logging and Tracking Experiments in Databricks
    Utilizing Databricks Notebooks for ML Experiments
  • **Databricks Feature Store**
  • Introduction to Feature Stores
    Managing Features in Databricks
    Feature Reusability and Sharing
  • **AutoML in Databricks**
  • Overview of AutoML
    Using Databricks AutoML for Automated Model Training
    Evaluating and Deploying AutoML Models
  • **Real-World Application and Case Studies**
  • Case Study: End-to-End Model Deployment
    Best Practices for ML Deployment
    Challenges and Troubleshooting in Production
  • **Conclusion and Future Trends**
  • Future Trends in ML Model Deployment
    Advanced Features in Databricks and MLflow
    Continuous Learning and Improvement Strategies

Subjects

Data Science