I will audit your machine learning notebook and create a deployment roadmap

Do you have a working machine learning notebook but no clear path to deployment?

I will review one existing Python ML notebook and assess how it can be turned into a maintainable API, batch prediction workflow, or broader MLOps solution.

The audit covers:

• code structure, preprocessing, training and prediction logic
• reproducibility, dependencies and model artifacts
• input/output requirements and deployment readiness
• API, batch and MLOps architecture options
• risks, blockers and missing components
• prioritized improvements and quick wins
• high-level effort estimates for implementation
• 
  

You will receive a project-specific written report including a deployment readiness score, key findings, recommended target approach, required improvements, and a practical step-by-step roadmap.

This Gig covers assessment and planning only. It does not include refactoring, debugging, API development, cloud deployment, CI/CD, monitoring, or pipeline implementation.

Please contact me before ordering for multiple notebooks, deep learning, custom infrastructure, sensitive data, or complex external dependencies.