End-to-end ML toolkit automating the complete workflow — data profiling, preprocessing, feature engineering, model selection, training, validation, explainability, drift monitoring, fairness checks, and interactive HTML reporting. Includes a full CLI for zero-code ML pipelines. Python 3.10+.

Autonomous multi-agent AI coding assistant as a JetBrains IDE plugin. Routes tasks through a Tolkien-themed fellowship (Gandalf→Aragorn→Celebrimbor→Samwise) with offline-first local Qwen inference, cloud fallback (Alibaba/Gemini/Amazon Q), and tools for code editing, terminal, git, web search, and project scanning.

Solutions and notebooks for data mining and machine learning competitions. Feature engineering, model stacking, hyperparameter tuning, and ensemble techniques.

Movie recommendation system using collaborative filtering and content-based approaches. Analysis of viewing patterns and genre preferences.

Sports score prediction using statistical models and machine learning. Time series analysis, Poisson regression, and ensemble methods for match outcome forecasting.

Health data analysis and personal wellness tracking. Statistical modeling of fitness metrics, sleep patterns, and nutrition data with interactive visualizations.