Tag: deployment

• How to train and deploy a machine learning model on AWS Sagemaker with ZenML and BentoML (14 Dec 2022)
  Learn how to use ZenML pipelines and BentoML to easily deploy machine learning models, be it on local or cloud environments. We will show you how to train a model using ZenML, package it with BentoML, and deploy it to a local machine or cloud provider. By the end of this post, you will have a better understanding of how to streamline the deployment of your machine learning models using ZenML and BentoML.
• Deploy your ML models with KServe and ZenML (04 Aug 2022)
  How to use ZenML and KServe to deploy serverless ML models in just a few steps.
• All Continuous, All The Time: Pipeline Deployment Patterns with ZenML (11 May 2022)
  Connecting model training pipelines to deploying models in production is seen as a difficult milestone on the way to achieving MLOps maturity for an organization. ZenML rises to the challenge and introduces a novel approach to continuous model deployment that renders a smooth transition from experimentation to production.
• How to painlessly deploy your ML models with ZenML (02 Mar 2022)
  Connecting model training pipelines to deploying models in production is regarded as a difficult milestone on the way to achieving Machine Learning operations maturity for an organization. ZenML rises to the challenge and introduces a novel approach to continuous model deployment that renders a smooth transition from experimentation to production.