M

machine-learning

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

Lightweight vector embeddings store for RAG applications

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.

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

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.

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

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.

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

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.

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

This is an extension integrated machine learning to provide security from scam and other phishing links and domains.

This is a steganography detector build on top of python and machine learning logic. User can enter their own dataset and train their own model. Also a future rich ui experience.

Academic NLP project focused on multilingual text summarization using Transformer-based deep learning models and natural language processing techniques.

AI-Powered YARA Rule Generator with LLM - By Ayi NEDJIMI

https://ayinedjimi-consultants.fr