Build a No Show Prediction Model and Deploy with FastAPI
Group: Capstone Project
Product Category: AI Engineering
Sub Category: MLOps Engineer
Solution Available
Source code, datasets, and other related files for the solution will be provided.
About this Product
Clinics lose revenue to no-show appointments; a notebook model can predict them, but it needs to become a governed service.
What you build
- Synthetic data generator: creates realistic appointment records for training and testing.
- Reproducible training pipeline: validates data, fits a scikit-learn model and records metrics and versions.
- Model package and checksum: versioned folder with the model file, metadata and SHA256integrity check.
- FastAPI prediction service: validates requests, scores appointments and returns risk bands and actions.
- Monitoring and drift detection: request log with latency, error rates and mean-shift drift flags.
Skills you practise
- Model governance: packaging, versioning, checksums and promotion gates.
- API design: request validation, error codes, response contracts.
- Experiment tracking: seeded reproducibility, run records with params and metrics.
Outcome
- Portfolio ready: a complete ML system that demonstrates model packaging, API design and monitoring in a real scenario.
Interview Q&A Included
1 practice set bundled with this lab
-
SlotSentry No Show Model Deployment and Monitoring Assessment
Category: AI Engineering Subcategory: ML Engineer 42 questionsThis assessment checks what you learned while turning a clinic's notebook no show model into a governed service. It is split into five groups that follow the lab: the business …
Resources
Step by step instructions to install, configure and run the project on Windows and macOS.
- Separate macOS and Windows parts, so you only follow the steps for your own computer
- What to install first: Python 3.11 or 3.12, with the command to check the version
- Creating the virtual environment and installing the pinned requirements
- The .env file and its settings, with safe defaults and no secrets to fill in
- Running the service, calling it, and what you should see at each step
- Running the tests, and fixes for the most common setup problems
Topics
Skills
Languages
English
Level
Beginner
Business Domain
Healthcare and Patient Management
Project Mentors
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