M

machine-learning

Data Science / Machine Learning Pipeline component for training and deploying ML models using CI

Official repository of the Ruhr university Neural Network energy representation (RuNNer).

Neural context compression for long-running AI agents. Query-aware context compiler.

A deterministic verification layer for AI systems. QWED verifies AI outputs using mathematics, symbolic reasoning, and formal methods (Z3, SMT, SymPy), creating an auditable trust boundary for agentic AI. Not generation. Verification.

PulseCheck is an open-source dynamic code intelligence platform that monitors and analyzes code at runtime. It detects TODOs, decoy or unused functions, anti-distillation tricks, and security/safety issues. Leveraging AI and machine learning, PulseCheck provides anomaly detection, predictive TODO analysis, behavior clustering, and runtime insights, giving developers actionable intelligence to secure, optimize, and complete their code from draft to deployed. https://roxanneardary.com/pulsecheck/

Lightweight vector embeddings store for RAG applications

Full stack IoT predictive maintenance platform with embedded firmware, sensor telemetry, FastAPI services, PostgreSQL storage, dashboards and anomaly detection.

Aston University DG1AID lab repository with AI and data science notes, Python notebooks, NumPy, Pandas, search algorithms and machine learning practice.

Finally a smart RSS reader which doesn't suck ass or your data.

Neural network experiments for Supercompress compression engine.

End-to-end predictive maintenance ML pipeline for hydraulic systems with Streamlit app, XGBoost models, SHAP, and real-world sensor data.

https://hydraulic-monitoring.streamlit.app/

About Behavioral finance meets machine learning. Early-warning system to forecast S&P 500 downturns using sentiment, volatility, and unemployment data — with SHAP explainability ,Gradio and Hugging Face deployment.

https://huggingface.co/spaces/Artur-Melnyk/Market-Mood-Forecasting

Explainable suburb similarity explorer built with Python, Streamlit, vector search and transparent model reasoning.

The AI and the Automobile collection brings together multiple specifications that define how AI integrates into modern vehicle systems, treating the automobile as a software-defined platform where intelligence spans perception, control, navigation, and energy management. It emphasizes real-time performance, safety-critical architecture, and the transition from purely mechanical systems to continuously evolving software-driven mobility. Across the collection, the specs also describe how automotive AI should be built through open and interoperable systems with strong safety practices, including simulation, validation pipelines, and human-in-the-loop oversight to handle edge cases. Together, they frame vehicle intelligence as a layered system combining autonomy, redundancy, diagnostics, and secure update mechanisms to enable reliable and scalable deployment.

RuNNerASE is a collection of packages for training, evaluating, and analyzing machine learning potentials with RuNNer, the Ruhr university Neural Network energy representation.

Curated open-source large language models, training frameworks, and evaluation resources.

Curated GPU cloud providers, platforms, and services for AI and accelerated computing workloads.

AI-Powered Anti-Cheat Research Tool - Train your own AI to detect suspicious gameplay patterns using Vision Transformers and audio analysis. Fully local processing, no cloud uploads. Perfect for competitive gaming research and anti-cheat development.

API4AI is cloud-native computer vision & AI platform for startups, enterprises and individual developers. This repository contains sample mini apps that utilizes People Photo Background Removal API provided by API4AI.

pt_kmeans is a high-performance, pure PyTorch K-Means implementation for CPU/GPU, featuring K-Means++ initialization, hierarchical clustering, and cluster splitting, optimized for large-scale datasets.