Model deployment is the next and very important steps once you finalized your model training and development. There are many methods available to deploy the models depending upon the type of serving. There are many serving methods like batch serving, online serving, real time serving or live streaming based serving. In this article I am going to explain one of the deployment mechanism which does online serving using APIs. So I will be explaining how to deploy models using Docker container and run them on production efficiently and reliably. Model Training – IRIS multi-classification Model ...…Model deployment is the next and very important steps once you finalized your model training and development. There are many methods available to deploy the models depending upon the type of serving. There are many serving methods like batch serving, online serving, real time serving or live streaming based serving. In this article I am going to explain one of the deployment mechanism which does online serving using APIs. So I will be explaining how to deploy models using Docker container and run them on production efficiently and reliably. Model Training – IRIS multi-classification Model ...WW…

If you are a devops engineer and working in this role for more than three years then you can easily switch to highly paid mlops engineer and double your salary. As you are already aware of devops practices, tools and techniques to achieve software deployment in production efficiently and reliably. So with little effort and learning few extra techniques which I will be talking in next paragraphs, you can simply become the mlops engineer where you start deploying machine learning models in production. You might already be doing the same thing still your role says you are a devops and you are...…If you are a devops engineer and working in this role for more than three years then you can easily switch to highly paid mlops engineer and double your salary. As you are already aware of devops practices, tools and techniques to achieve software deployment in production efficiently and reliably. So with little effort and learning few extra techniques which I will be talking in next paragraphs, you can simply become the mlops engineer where you start deploying machine learning models in production. You might already be doing the same thing still your role says you are a devops and you are...WW…