Full-Stack 2025-11 Featured
Cloud NLP Classification Service
Production-ready multi-model text classification service with zero-downtime model switching, deployed on GCP. DistilBERT achieves 96.57% accuracy.
96.57% Accuracy
NLPDistilBERTFastAPIDockerGCPPyTorch
Overview
A production-grade multi-model text classification service built with FastAPI and Docker, featuring zero-downtime model switching between DistilBERT, TF-IDF + LogReg, and TF-IDF + SVM. Deployed live on GCP Compute Engine using an e2-standard-2 instance.
Model Benchmarks
| Model | Accuracy | Latency | Cost Factor |
|---|---|---|---|
| DistilBERT | 96.57% | 60–100ms | Baseline |
| LogReg (TF-IDF) | 85–88% | 5ms (21× faster) | — |
| SVM (TF-IDF) | 85–88% | 2ms (44× faster) | — |
Trained and benchmarked on a 24,783-sample dataset with comprehensive E2E validation.
Key Features
- Zero-Downtime Switching: Hot-swap between models without service interruption
- 326+ Test Suite: Automated E2E validation with 100% pass rate
- Cloud Deployment: Live on GCP at
$0.07/hr ($50/mo) - Multi-Model Architecture: Pluggable model backends behind a unified API
Tech Stack
- ML: Hugging Face Transformers, PyTorch, scikit-learn, TF-IDF
- API: FastAPI, Uvicorn, Pydantic
- Infrastructure: Docker, GCP Compute Engine (e2-standard-2)
- Testing: pytest, 326+ automated tests