Machine Learning Model Deployment with FastAPI

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8 janvier 2026 • 1 min de lecture
Machine Learning Model Deployment with FastAPI

1.FastAPI for ML

FastAPI is perfect for serving ML models with high performance.

2.Basic Setup

from fastapi import FastAPI import joblib app = FastAPI() model = joblib.load('model.pkl') @app.post("/predict") async def predict(data: dict): prediction = model.predict([data['features']]) return {"prediction": prediction.tolist()}

3.Docker Deployment

FROM python:3.9 WORKDIR /app COPY requirements.txt . RUN pip install -r requirements.txt COPY . . CMD ["uvicorn", "main:app", "--host", "0.0.0.0"]

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