Machine Learning Model Deployment with FastAPI
Deploy ML models to production using FastAPI and Docker.

FastAPI for ML
FastAPI is perfect for serving ML models with high performance.
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()}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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