Synthetic test data that hits the numbers you declare, exactly. Multi-table with verified foreign-key integrity, deterministic, no model in the data path. Python + MCP server.
High-performance interpretable ML classifier using High Utility Gain patterns (IEEE Access 2024). C++ accelerated, scikit-learn compatible, with EBM-style explanations, adaptive binning, pattern pruning, and deployment tooling for regulated domains.
🦦 Pandas-style DataFrame library for Go — fluent API for filtering, grouping, sorting, and statistical analysis with type-safe operations and zero-copy typed slice access.