S

scikit-learn

A production-grade machine learning system for classifying celestial objects — stars, galaxies, and quasars — from 500,000 photometric observations sourced from the Sloan Digital Sky Survey (SDSS DR18). The pipeline covers LOF-based outlier detection, SMOTEENN class balancing, and SelectKBest feature selection, with six classifier configurations benchmarked against each other. Random Forest achieved the highest accuracy at ~99.51%, while LightGBM was selected for deployment due to its faster inference, smaller footprint, and clean ONNX export path. The system is fully containerized with Docker, backed by a CI/CD pipeline, and served live via a Gradio interface on Hugging Face Spaces.

A set of data machine learning/deep learning projects exploring various datasets — a place to test ideas, models, and modern stacks.

Slimme huishoudboekje-app met AI-gestuurde categorisering. Importeer je ING/Revolut transacties, krijg automatisch inzicht in je uitgaven en beheer je budget met NIBUD-referenties. Privacy-first: alle ML draait lokaal.

Volledige ge amp/vibe coded met Claude Code!

Code and data for Natural Language Processing in Action, 2nd Edition, by Maria Dyshel and Hobson Lane for Manning Publications

this project it to practice all concepts and knowledge in the course mlops-zoomcamp

PI de la Carrera de Ingeniería en Computación 2021 - FCEFyN (UNC)