M

machine-learning

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

Self-hosted forecasting + prediction service. Five zero-shot time-series foundation models (Chronos-2, TimesFM 2.5, Moirai-2, Toto-1, Sundial) across six forecast types, plus nine supervised tabular ML backends (LightGBM, XGBoost, sklearn family) with calibrated / stacking / diversified meta-learners. Unified REST API + MCP server.

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.

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

Multi-source RAG pipeline with hybrid vector + keyword retrieval, LLM-powered concept knowledge graph, adaptive search weighting, and evaluation framework.

Deep learning system for seismic velocity inversion using a SincNet-GAT-UNet architecture, physics-informed temporal encoding, graph attention fusion, and FiLM-conditioned spatial prediction

The efficient alternative to Neural Networks. Implements SLRM (Segmented Linear Regression Model) for neural compression and non-linear data modeling, achieving high precision with a fraction of the parameters of a traditional ANN.

BrotServer é um projeto de Modern Data Stack on‑premise que integra hardware de nível empresarial (Dell PowerEdge T440) e a plataforma open source Cloud Brots para desenvolvimento, ciência de dados, BI, IA e ensino. O repositório versiona o livro técnico oficial, que documenta a arquitetura, os padrões de Ops (GitOps, DataOps, ModelOps, ResearchOps, AIOps), os componentes principais (Kubernetes/RKE2, Longhorn, Traefik, MinIO, PostgreSQL, Superset, Moodle, Ollama, etc.) e as boas práticas de operação, com foco em soberania de dados, reprodutibilidade científica e uso de uma única porta de acesso.

AI-powered automation of macOS Apple applications

This is a proof of concept to learn about AI and MacOS, and developed using with AI. I am unlikely to progress this any further.

mcp-mac enables AI agents to interact with macOS applications (Finder, Mail, Contacts, etc) using AppleScript through the Model Context Protocol (MCP).

This allows AI assistants to perform tasks like searching contacts, managing files, and checking email on your behalf.

Project information This is the final source code for my model deployment—a Streamlit application for the Netflix Movie Recommendation System, or we can use the Flask framework. The complete model training, exploratory data analysis (EDA), and data preprocessing are available in my GitHub repository.

GitHub: github.com/aydiegithub/

Live Demo: aydie.in/ml/netflix-recommendation

Contact: business@aydie.in 9036469492 aydie.in

Moodle Plugin repository for recommending courses based on machine learning predicting, and a dashboard to monitor courses and users. Made by Diva Alfiah as a thesis project.

Auctions & bids online live system

An Active Learning framework for Drug Discovery with the ability to create targeted models for particular experiments