ai-machine-learning

Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application

oneAPI Data Analytics Library (oneDAL)

oneAPI Collective Communications Library (oneCCL)

The easiest way to use Machine Learning. Mix and match underlying ML libraries and data set sources. Generate new datasets or modify existing ones with ease.

A Complete Resource to Master Graduate-Level GenAI Mathematics

Beginner → Intermediate (Student & Self-Learner Friendly)

Software-based rationalia. A structured "Wikipedia for arguments" leveraging collective intelligence to automate enlightenment, conflict resolution, and cost-benefit analysis. This platform revolutionizes political and societal debates through logical ranking, pro/con organization, and rigorous, systemic evaluation frameworks and sustainable logic.

Texas Longhorns baseball intelligence for scouting, roster evaluation, and SEC analysis. Integrates program doctrine with live MCP data from the college-baseball-sabermetrics server. Optimized for data-backed reports and historical comparisons.

An AI-powered content moderation system using Python and Hugging Face Transformers. Combines rule-based filtering and machine learning to detect and block toxic, profane, and politically sensitive content, built for developers and communities to create safer, positive online spaces.

🤖 RAG-based chatbot that extracts knowledge from PDF documents, retrieves relevant context, and generates accurate answers using LLMs.

AI-powered symptom checker with triage recommendations and symptom pattern tracking — FastAPI backend using lightweight NLP and ML models. MVP-ready for health-tech innovation.

Personal AI/ML portfolio demonstrating Python projects with hands-on machine learning, front-end, and back-end development skills.

QLX AI Powered ML System is a demo web application that uses machine learning to analyze and predict data from a database. You can user any LLM provider

AI Simulation

AI CDSS predicting respiratory patient risk from EHR and imaging data, with clinically actionable outputs.

aims to understand the characteristics, structure, and important components of the dataset and learning process by giving marked data to the model.

Full Scholarship Comp. Eng. Student at BAU. Building expertise in Full-Stack Web Dev & AI/ML with Python OOP and clean Git practices.

This is my solutions to Datacamp projects.

A cutting-edge AI-powered facial recognition attendance system that automates tracking in educational institutions and workplaces

This project analyzed documented UFO sightings by examining trends, identifying active states, categorizing sightings, and mapping patterns across the U.S. Predictive modeling then forecasted sightings by state and shape, offering valuable insights for researchers and enthusiasts alike.