8 boosters for "experiments" — open source, verified from GitHub, ready to install
Experiment Tracker is an AI agent that helps teams design, execute, and analyze A/B tests and feature experiments using data-driven methodology. Product managers, data scientists, and engineers use it to validate hypotheses and make statistically-grounded decisions.
Helps developers quickly create structured, reproducible Jupyter notebooks for experiments and tutorials using built-in templates and helper scripts. Ideal for data scientists, researchers, and educators who need consistent notebook scaffolding.
Run any workload on fully managed Hugging Face infrastructure. No local setup required—jobs run on cloud CPUs, GPUs, or TPUs and can persist results to the Hugging Face Hub. Use this skill when users want to: When assisting with jobs:
Trackio is an experiment tracking library for logging and visualizing ML training metrics. It syncs to Hugging Face Spaces for real-time monitoring dashboards. Use in your training scripts to log metrics: → See references/logging_metrics.md for setup, TRL integration, and configuration options.
Trackio is an ML experiment tracking library that integrates with Hugging Face to log metrics, visualize training progress, and trigger alerts during model development. It's useful for ML engineers and researchers who need real-time monitoring and experiment management.
This skill enables users to run Python workloads, Docker jobs, and GPU-intensive tasks on Hugging Face's managed infrastructure without local setup. It's valuable for ML engineers, data scientists, and developers needing cloud compute for training, inference, and batch processing.
pycse is a Python library that assists with scientific computing tasks including nonlinear regression, uncertainty quantification, design of experiments, and neural network-based modeling. It's useful for researchers, engineers, and data scientists working on numerical optimization, experimental design, and uncertainty analysis.
This MCP Server enables seamless integration with GrowthBook, allowing developers to manage feature flags, experiments, and A/B tests directly through Claude. It's essential for product teams and engineers who use GrowthBook for feature management and experimentation workflows.
