Technical writing, data analysis notebooks, and research on data science, machine learning, and system optimization.
Deep dive into deploying a production ML forecasting system processing 542,000 rows/second with real-time regime detection, async service architecture, and comprehensive health monitoring.
Deep dive into optimizing a production trading system's database initialization from 6.6 seconds to 8.2ms, unblocking 37 critical features and restoring real-time trading capability.
Complete technical reference for deploying machine learning models to production, covering serving architectures, containerization, lifecycle management, performance optimization, and operational monitoring.
Comprehensive reference for optimizing database performance in production systems, covering SQLite configuration, schema design, indexing strategies, transaction management, and monitoring.
Comprehensive reference for database optimization techniques, from predicate pushdown to result caching. Includes performance impact tables and code examples.
How a custom Rust query engine replaced DuckDB and achieved 10.4x speedup through predicate pushdown. Covers 5 optimization iterations with real metrics.
Learn how to create stunning data visualizations inspired by iconic films using the Cinestyle library. From Film Noir to Star Wars, transform your matplotlib charts into cinematic masterpieces.
Complete guide to deploying machine learning models in production
Learn how to create high-performance, interactive data visualizations in the browser using Rust compiled to WebAssembly.
How I built an AI-powered data pipeline that extracts 296 businesses from Chamber of Commerce directories in 9 minutes, achieving 100% name/phone capture using local LLMs and intelligent web scraping.