Accelerating mlflow 2.0 Pipelines for Production using Databricks

Achieve Easy Experimentation, Reproducibility, and Deployment with MLflow 2.0

Mlflow 2.0 – a more advanced version of MLflow – is being rolled out by Databricks to standardize, accelerate, and productionalize the Machine Learning model development process. This best-of-the-breed platform will provide production-grade ML pipelines and ready-made templates to enable practitioners to

  • Achieve faster iterative development
  • Speed up the production and deployment of ML models at scale
  • Do without writing the boilerplate code
  • Ensure reproducibility of pipelines
  • Build models that serve in different environments
  • Maintain a central storage space for all their model versions
  • Draw quick comparisons of results at the workflow level

Royal Cyber is making it possible for you to get familiar with MLFlow by giving a free demo on the platform & our data experts successfully build efficient and high-performing Machine Learning models using MLflow 2.0.

Watch On-Demand


Hassan Sherwani

Hassan Sherwani

Head of Data Analytics & Data Science
at Royal Cyber
Mehroz Alam

Mehroz Alam

Data Scientist at Royal Cyber


An Introduction to MLOps and MLFlow 2.0

Features of MLflow 2.0 Platform

Missing Components in Data Science ML Practice

Live Demo

Question & Answer Session

Accelerating mlflow 2.0 Pipelines for Production using Databricks