by Pronay Ghosh and Hiren Rupchandani

• In the previous article, we saw how to deploy a machine learning model into the local box.
• Now, we will be deploying the model on Amazon EC2.
• Before doing that, let’s first set up the environment for our trained machine learning model.
• This can…

By Hiren Rupchandani, Abhinav Jangir, and Ashish Lepcha

Till now we have developed a model, deployed it using a flask app as well as on GCP, and containerized our flask app using Docker Desktop.

Now it is time to prepare the containerized app for scaling. And how will we achieve…

by Pronay Ghosh and Hiren Rupchandani

• In the previous article, we saw what are the different types of AWS Services.
• Now is the time to deploy a machine learning model into Amazon EC2.
• However, in order to do so, we will first have to deploy our machine learning model into…

By Hiren Rupchandani, Abhinav Jangir, and Ashish Lepcha

• Container deployment is a popular technology that gives developers the ability to construct application environments with speed at scale.
• Containerization is OS-based virtualization that creates multiple virtual units in the userspace, known as Containers.
• Containers share the same host kernel but are…

by Pronay Ghosh, Hiren Rupchandani

In the previous article, we understood what exactly cloud computing is all about through Amazon Web Services, and in this article, we will be focussing on the following key topics

• AWS Management Console: which is typically the dashboard where one can perform all of the…

by Pronay Ghosh and Hiren Rupchandani

• A case study from IBM reveals that an average aircraft generates between 500 to 1,000 gigabytes of data on a daily basis.
• Since the evolution of data science has come into the picture, the main constraint was to store large-scale data.
• However, over time…

By Hiren Rupchandani, Abhinav Jangir, and Ashish Lepcha

• ML models require deployment to a production environment to provide business value.
• But the unfortunate reality is that many models never make it to production, or if they do, the deployment process takes much longer than necessary.
• Even successfully deployed models will…

By Hiren Rupchandani, Abhinav Jangir, and Ashish Lepcha

Now that our model is ready to be deployed, this article will cover how we can locally deploy it using flask. Before proceeding, let’s refresh on the basics of deployment.

• Deployment is defined as a process through which you integrate a machine…