🌱 From Machine Learning Model to API Testing

This is one of my recent projects where I integrated a TensorFlow Lite (TFLite) leaf disease classification model with a Python-based Flask application and tested the model inference through Postman.

The current prototype allows an image to be sent to the application, processed by the TFLite model, and returned with a predicted leaf disease classification. I’m currently working on the API integration and testing stage as part of the process of turning the trained ML model into a service that can eventually be integrated into a mobile or web application.

🛠️ Technologies & Tools • Python • Flask • TensorFlow Lite (TFLite) • Machine Learning / Image Classification • REST API Development • Postman • Android Integration — planned next

This project is helping me build practical experience in taking a trained machine learning model beyond the notebook and preparing it for real-world application integration.

I'm interested in projects involving Android development, machine learning integration, AI-powered applications, REST APIs, and intelligent mobile solutions.

🚀 Have an ML model that you want to integrate into an application? Let's connect.