Standardized Distributed Generative and Predictive AI Inference Platform for Scalable, Multi-Framework Deployment on Kubernetes

A platform-neutral analytical skill that profiles messy data, selects adaptive methods, and produces source-backed visual reports for high-stakes decisions.

A principles-first workflow for AI coding agents providing reusable phases and end-to-end workflows for software development tasks.

Retentioneering: product analytics, data-driven CJM optimization, marketing analytics, web analytics, transaction analytics, graph visualization, process mining, and behavioral segmentation in Python. Predictive analytics over clickstream, AB tests, machine learning, and Markov Chain simulations.

Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.

Performance analysis of predictive (alpha) stock factors

Open-source framework for uncertainty and deep learning models in PyTorch 🌱

Sports sponsorship intelligence platform for World Cup match data, real-source text signals, ROI prediction, uncertainty analysis, and scenario recommendations.

A self-interrogation skill packaging 697 senior-engineer questions as a portable Claude/Codex skill and prompt to improve agent reasoning before writing code.

[CVPR 2024 Highlight] GenAD: Generalized Predictive Model for Autonomous Driving

Quantify uncertainty and sensitivities in your computer models with an industry-grade Monte Carlo library.

OpTaS: An optimization-based task specification library for trajectory optimization and model predictive control.