How to Build A Machine Learning API Using Flask

How to Build A Machine Learning API Using Flask

This tutorial will show you how to build a REST API for machine learning model using Flask. Learn how to build a machine learning API using Flask. Also, I will explain the basic concept of REST API.

Machine Learning (ML) is a great way to do tasks that cannot be explicitly coded, for example, image classification. But when the model is already built, it will be useless when we don’t deploy it into an application.

Deployment is an essential step in the machine learning workflow. It is a step where we want to apply our ML model into an application. Afterwards, we can use the model in real life.

But how can we create the model as an application? We can build an Application Programming Interface (API). With that, we can access the model from everywhere, whether it is on the mobile application or even on the web application. In Python, there’s a library that can help us to build an API. It’s called Flask.

This article will show you how to build a REST API for our machine learning model using Flask. Without further ado, let’s get started!

machine-learning deep-learning data-science flask python

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