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ExplaineR is an R package built for enhanced interpretation of classification and regression models based on SHAP method and interactive visualizations with unique functionalities so please feel free to check it out, See ExplaineR paper at doi:10.1093/bioadv/vbae049
Real-time reward debugging and hacking detection for reinforcement learning
π cookiecutter-modern-ml
Ultramodern ML cookicutter
π§ NeuroForge is an intuitive drag-and-drop tool for building and training neural networks, featuring data preprocessing, interactive visualizations, and automated model architecture design. Built with PyTorch and Streamlit, it simplifies the deep learning workflow from data preparation to model deployment with GPU acceleration support.
Can be used to spin-up mojaloop and make test transfers (P2P, etc) using TTK. This repo can also be used for functional tests in the core services.
Medical artificial intelligence toolbox (MAIT): an explainable machine learning framework for binary classification, survival modelling, and regression analyses
π₯§ Complete ML development toolkit & template: Intelligent lazy loading (96% faster startup), Docker deployment guides, advanced prompt engineering, production project structure
Understanding AI and ML, using them
Github and general tools for the Mojaloop Community
Shared config for Mojaloop CI/CD Pipelines
π The Ultimate Curated List of LLMOps Tools, Frameworks, and Resources - A comprehensive collection of the best tools for Large Language Model Operations
A project template for new mojaloop services and libraries that uses Typescript.
Mojaloop repository NodeJs version checker
ScrollScribe is a Python CLI toolkit that grab docs or index website pages and converts them into clean local Markdown using browser automation and LLM filtering, perfect for building RAG datasets.
MLGuard β Lightweight ML experiment manager and leakage detection toolkit
RetroML is a nostalgic, configuration-driven AutoML pipeline that brings a β90s flair to modern machine learning workflows. It allows users to run ML classification tasks via JSON configs, with optional support for interactive UIs and demos (e.g., customer churn prediction).
CircleCI Orb for workflows, pipelines
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