Initial Commit 🚀

Author: pH-7

.DS_Store

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+FROM python:3.11-slim
+
+WORKDIR /app
+COPY requirements.txt .
+RUN pip install -r requirements.txt
+
+COPY . .
+
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]

Dockerfile

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+# 🚀 Logistic Regression API
+
+ML API that predicts binary classes using scikit-learn and FastAPI.
+
+- [x] Model trained on breast cancer dataset
+- [x] REST API with FastAPI
+- [x] Docker support
+- [x] Built by [Pierre-Henry Soria](https://pierrehenry.be)
+
+## 🔋 Run Locally
+
+```bash
+cd train/
+python train_model.py
+
+cd ..
+uvicorn app.main:app --reload
+```
+
+## 🐟 Docker
+
+```bash
+docker build -t ml-api .
+docker run -p 8000:8000 ml-api
+```
+
+Visit `http://127.0.0.1:8000/docs` for Swagger UI.
+
+
+## 👋 Author
+
+[![Pierre-Henry Soria](https://avatars0.githubusercontent.com/u/1325411?s=200)](https://ph7.me "Pierre-Henry Soria, Software Developer")
+
+Made with ❤️ by **[Pierre-Henry Soria](https://pierrehenry.be)**. A super passionate & enthusiastic Problem-Solver / Senior Software Engineer. Also a true cheese 🧀, ristretto ☕️, and dark chocolate lover! 😋
+
+[![@phenrysay](https://img.shields.io/badge/x-000000?style=for-the-badge&logo=x)](https://x.com/phenrysay "Follow Me on X") [![pH-7](https://img.shields.io/badge/GitHub-100000?style=for-the-badge&logo=github&logoColor=white)](https://github.com/pH-7 "My GitHub") [![YouTube Video](https://img.shields.io/badge/YouTube-FF0000?style=for-the-badge&logo=youtube&logoColor=white)](https://youtu.be/cWBuZ4DXGK4 "YouTube SucceedAI Video") [![Bluesky](https://img.shields.io/badge/bluesky-1e90ff?style=for-the-badge&logo=data:image/svg+xml;base64,PHN2ZyBmaWxsPSIjMDAwMDAwIiBoZWlnaHQ9IjI0cHgiIHZpZXdCb3g9IjAgMCAzMiAzMiIgd2lkdGg9IjI0cHgiIHhtbG5zPSJodHRwOi8vd3d3LnczLm9yZy8yMDAwL3N2ZyI+PHBhdGggZD0iTTMwIDZsLTIuOTk5LTEuNjY2TDMyIDMuMzQgMjMuMTg5IDAgMTYuMDA2IDUuMzQgOC44MTMgMCAwIDMuMzQgNC45OTkgNC4zMzQgMCA2bDUuMDAxIDQuODAzTDQgMjAuODFWMjRsNS4wMDEtMS42NjZMMTYgMjhMMjIuOTk5IDIyLjM0IDMyIDI0di0zLjE4OUwyNy4wMDIgMTIgMzAgNiIgLz48L3N2Zz4=)](https://bsky.app/profile/ph7s.bsky.social "Bluesky Profile")

README.md

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+from fastapi import FastAPI
+from app.schemas import PredictionInput
+from app.model import predict
+
+app = FastAPI()
+
+@app.post("/predict")
+def get_prediction(input: PredictionInput):
+    result = predict(input.data)
+    return {"prediction": result}

app/main.py

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+import joblib
+
+model = joblib.load("model/logistic_model.pkl")
+
+def predict(data):
+    prediction = model.predict([data])
+    return int(prediction[0])

app/model.py

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+from pydantic import BaseModel
+
+class PredictionInput(BaseModel):
+    data: list[float]

app/schemas.py

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+fastapi
+uvicorn
+scikit-learn
+joblib
+pydantic

requirements.txt

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+from sklearn.datasets import load_breast_cancer
+from sklearn.linear_model import LogisticRegression
+from sklearn.model_selection import train_test_split
+import joblib
+import os
+
+data = load_breast_cancer()
+X_train, X_test, y_train, y_test = train_test_split(data.data, data.target)
+
+model = LogisticRegression(max_iter=10000)
+model.fit(X_train, y_train)
+
+os.makedirs('../model', exist_ok=True)
+joblib.dump(model, '../model/logistic_model.pkl')