MLOps in R: Deploying machine learning models using vetiver

Did you know that over 70% of machine learning models never make it into production? Are you ready to defy the odds and become a master at deploying machine learning models in R? This Guided Project was created to help data professionals accomplish efficient model deployment using Vetiver in R. More specifically, in this 2-hour long project-based course, you will learn how to build an ensemble model, set up the deployment framework, deploy the model using various methods, and monitor model performance. To achieve this, you will create a fully automated deployment pipeline by working through a realistic scenario of deploying a hospital readmission model in a healthcare setting. This project is unique because it combines hands-on experience with the aim to bridge the gap between machine learning development and production deployment. In order to be successful in this project, you will need a solid understanding of R programming, basic machine learning concepts, and familiarity with building machine learning models using tidymodels.

• Project Overview
• Did you know that over 70% of machine learning models never make it into production? Are you ready to defy the odds and become a master at deploying machine learning models in R? This Guided Project was created to help data professionals accomplish efficient model deployment using Vetiver in R. More specifically, in this 2-hour long project-based course, you will learn how to build an ensemble model, set up the deployment framework, deploy the model using various methods, and monitor model performance. To achieve this, you will create a fully automated deployment pipeline by working through a realistic scenario of deploying a hospital readmission model in a healthcare setting. This project is unique because it combines hands-on experience with the aim to bridge the gap between machine learning development and production deployment. In order to be successful in this project, you will need a solid understanding of R programming, basic machine learning concepts, and familiarity with building machine learning models using tidymodels.