https://github.com/dsrathore1/iris-flower-classifier-api
A production-style API that predicts the species of an Iris flower based on input features using a trained Random Forest classifier. Fully containerized using Docker.
https://github.com/dsrathore1/iris-flower-classifier-api
dataset devops docker good-first-issue iris ml mlops
Last synced: 4 months ago
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A production-style API that predicts the species of an Iris flower based on input features using a trained Random Forest classifier. Fully containerized using Docker.
- Host: GitHub
- URL: https://github.com/dsrathore1/iris-flower-classifier-api
- Owner: dsrathore1
- Created: 2025-07-10T07:14:16.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2025-07-10T11:14:27.000Z (6 months ago)
- Last Synced: 2025-09-02T08:44:14.942Z (5 months ago)
- Topics: dataset, devops, docker, good-first-issue, iris, ml, mlops
- Language: Python
- Homepage:
- Size: 87.9 KB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🌸 Iris Flower Classifier API (FastAPI + Docker)
A production-style API that predicts the species of an Iris flower based on input features using a trained Random Forest classifier. Fully containerized using Docker.
## 🚀 Features
- FastAPI backend
- Dockerized deployment
- Iris dataset (scikit-learn)
- Prediction with class names
- Input validation
- Swagger UI at `/docs`
## 🔧 Technologies
- Python, FastAPI, scikit-learn, joblib
- Docker
- curl / Swagger UI
## 📦 Setup
```bash
# Train model
python train_model.py
# Build Docker image
docker build -t prayagraj55/basic_mlops_project.
# Run container
docker run -p 8000:8000 -d --name mlops-container prayagraj55/basic_mlops_project