Portfolio
Real documentation projects showcasing structured, developer-friendly technical writing for AI and ML APIs.
Comprehensive documentation for an AI-powered text classification API — designed from scratch as a demo concept. Covers full REST API documentation including authentication, endpoint references, error handling, and working code examples in cURL and Python.
Full REST API specification with request/response examples
Authentication flow and API key management
Error codes, status handling, and troubleshooting guide
cURL and Python code samples
AI behavior and confidence score explanation
JSON request/response schema documentation
Developer documentation for the ProsusAI FinBERT API — a real, live Hugging Face model fine-tuned on financial text. All API calls were tested hands-on in Postman. Covers authentication, endpoint reference, batch inputs, confidence score interpretation, and model limitations.
Live API tested in Postman with real responses
Single and batch input documentation
Confidence score interpretation table
cURL and Python code samples
Model limitations and best practices
Full error reference and troubleshooting guide
Developer documentation for an AI-powered medical image classification API built on a real deep learning model developed as a final year research project. The model detects sickle cell disease from blood smear images with 93.91% accuracy. Documentation covers three endpoints, batch analysis, image requirements, and model performance details.
Based on a real TensorFlow model — 93.91% accuracy
Three endpoint references: analyze, batch, and model info
Base64 image encoding and input requirements
cURL and Python code samples
Model performance table and limitations
Medical disclaimer and responsible AI guidance