Machine Learning Model Deployment Using Flask - Flask Tutorial

Machine Learning is such an intriguing niche. Also, it’s getting popular day by day. It’s a booming field with many opportunities. All you need is a little hard work to get started with it and with the help of our amazing courses and live sessions, we’re always here to help you. Getting a step ahead is when we deploy the Machine Learning Model. Today, we have come up with a tutorial on Machine Learning Model Deployment using Flask.

The Deployment of a Machine Learning Model is a key aspect of every Machine Learning project. Model Deployment is also one of the core topics that interviewers are keen to ask. Model Deployment can be referred to as the last stage of any project. After the completion of our project, we want our model to be available for the end-users so that they can make use of it. Here Flask plays an important role.

Flask is a web application framework written in Python. Flask gives users a variety of choices for developing web applications. Also, it provides the necessary tools and libraries that allow us to build a web application. It has multiple modules that make it easier for a web developer to write applications without having to worry about the details like protocol management, thread management, etc. To know more about how you can deploy your Machine Learning Model using Flask, Do watch the complete tutorial.

- Introduction.
What is Model Deployment.
Key Features of Model Deployment Architecture.
Architecture Comparison.
Model Deployment Options.
Model Deployment Platforms.
Case Study 1.
What is Flask?.
Steps to Deploy Application using Flask.