pandudcau / flask-projects-dcau

Machine learning model deployment, also known as putting models into production, refers to making your models available to end users or systems. The deployment of machine learning models, on the other hand, is complicated. This post will show you how to use the Flask API to bring your trained machine learning models into production.

Flask Web Applications

Flask is a Python API that allows us to create web-based applications. Flask's framework is more clear than Django's, and it's also easier to learn because it requires less basic code to create a simple web application. A Web-Application Framework, often known as a Web Framework, is a set of modules and libraries that allow programmers to create apps without having to write low-level code like protocols and thread management.

Basic Structure of the Flask Application

1. Creating your frontend for your Application

template Folder

2. Additional Styling files will be included

Static Folder

3. Testing suite

Test folder

4. Virtual Environment

Deployment of the Application

1. Run this Command in your cmd for depolyment of flask

python app.py