DJ-ML: Iris Classification with Django and Machine Learning

DJ-ML is a repository that showcases an Iris classification model using Django and machine learning. It leverages Django's features to seamlessly integrate with machine learning models for predictive analytics in web applications.

Features of Django for Machine Learning Integration

• ORM (Object-Relational Mapping): Django's ORM simplifies database interactions, enabling easy storage and retrieval of data from machine learning models[5].

• Scalability: Django supports scalability through container deployment, facilitating the deployment of machine learning models within scalable environments[4].

• User Interface: Django provides tools for creating user interfaces, allowing for user interaction with machine learning models deployed in web applications[4].

• REST API Integration: Django can be used to create REST APIs that connect with machine learning models, enabling the deployment of predictive analytics in web applications[5].

By utilizing these features, Django can effectively connect with machine learning models, enabling the seamless integration of predictive analytics and machine learning functionalities within web applications.

Tech Stack

• Python 3.6
• Django 2.2.4
• Machine Learning model