zemlyansky

Make synthetic datasets

InterpretML EBM (Explainable Boosting Machine) compiled to WebAssembly -- interpretable ML in browsers and Node.js

Streaming ETL language + runtime

JavaScript Execution Environment

ARIMA, SARIMA, SARIMAX and AutoARIMA models for time series analysis and forecasting

Probabilistic programming library powered by TensorFlow.js

StatSim execution engine — orchestrates stoch + jsee for running compiled models

Tsetlin Machine compiled to WebAssembly -- interpretable ML in browsers and Node.js

Permutation feature importance

Mitra Tab2D in-context learning model as a wlearn Estimator (ONNX Runtime)