{"repo":"SelfExplainML/PiML-Toolbox","free":true,"listed":false,"github":"https://github.com/SelfExplainML/PiML-Toolbox","clone":"git clone https://github.com/SelfExplainML/PiML-Toolbox.git","description":"PiML (Python Interpretable Machine Learning) toolbox for model development & diagnostics","language":"Jupyter Notebook","stars":1286,"topics":["interpretable-machine-learning","low-code","ml-workflow","model-diagnostics"],"license":"Apache-2.0","category":"workflow-automation","readme_excerpt":"An integrated Python toolbox for interpretable machine learning --- March 30, 2025 by Dr. Agus Sudjianto : Farewell PiML, Hello MoDeVa! After three impactful years of empowering model developers and validators, we’re thrilled to introduce the next evolution: MoDeVa – MOdel DEvelopment & VAlidation. MoDeVa builds on the success of PiML, taking transparency, interpretability, and robustness in machine learning to a whole new level. Whether you’re in a high-stakes regulatory setting or exploring cutting-edge model architectures, MoDeVa is built to support your journey. Why MoDeVa? • Next-Gen Models: Interpretable ML models like Boosted Trees, Mixture of Experts, and Neural Trees—built for confident decision-making. • Model Hacking Redefined: Tools to uncover failure modes, analyze robustness, reliability and resilience. • Interactive Statistical Visualizations: Bring models to life with dynamic graphs that go beyond static charts. • Seamless Validation: Effortlessly validate external black-box models using flexible wrappers. Check it out here: https://modeva.ai/ --- pip install PiML 🎄 Dec 1, 2023: V0.6.0 is released with enhanced data handling and model analytics. :rocket: May 4, 2023: V0.5.0 is released together with PiML user guide. :rocket: October 31, 2022: V0.4.0 is released with enriched models and enhanced diagnostics. :rocket: July 26, 2022: V0.3.0 is released with classic statistical models. :rocket: June 26, 2022: V0.2.0 is released with high-code APIs. :loudspeaker: ","default_branch":null,"files":null,"tree":[],"storefront":"/r/SelfExplainML","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/SelfExplainML/PiML-Toolbox/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}