
End-to-End MLOps & Machine Learning Pipeline Development
Starting at
$
35
/hrAbout this service
Summary
What's included
MLOps Architecture & Plan
A clear system design covering data flow, training pipeline, model registry/versioning, deployment approach, and monitoring strategy.
Reproducible Training Pipeline
Modular ML/DL training pipeline (data prep → train → evaluate) with configurable parameters and repeatable runs.
Experiment Tracking & Model Versioning
Setup for tracking experiments, metrics, artifacts, and model versions (e.g., MLflow/DVC) to ensure reproducibility.
Model Evaluation Report
Evaluation summary with metrics, validation results, error analysis, and recommended improvements.
Deployment-Ready API (Dockerized)
A production-ready inference API (FastAPI/Flask) packaged with Docker for consistent deployment.
CI/CD Automation
Automated build/test/deploy pipeline (e.g., GitHub Actions) to ship updates reliably and reduce manual work.
Monitoring & Logging Setup
Monitoring-ready integration (logs + metrics + basic drift hooks/alerts) for ongoing reliability in production.
Documentation & Handover
Clear README + runbook (setup, training, deployment, troubleshooting) with a guided handover session.
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