Finding Donors, CharityML, a Supervised Learning Machine Learning Project.
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Updated
Mar 17, 2026 - HTML
Finding Donors, CharityML, a Supervised Learning Machine Learning Project.
End-to-end customer churn analysis and prediction using Python, Machine Learning, and Power BI with actionable business insights.
Machine learning API for Iris classification built with FastAPI and scikit-learn.
This project is a production-ready text classification system built using BERT. It takes raw text input (e.g., customer issues) and predicts the most relevant category along with a confidence score.
An AI-powered Endpoint Detection and Response (EDR) simulation.
An end-to-end breast cancer tumor stage prediction system leveraging machine learning, clinical and genomic data, and a Flask-powered web interface to deliver accurate, real-time predictions.
Medical condition prediction using TensorFlow neural network classifies patient conditions from clinical data using NLP-based text encoding and deep learning.
Machine learning model for predicting diabetes using medical data, demonstrating an end-to-end ML pipeline with training, evaluation, and model persistence.
Multi-role AI agent system — customer service, HR portal & owner dashboard — built with LangGraph, GPT-4o, RAG, and ML predictions. Arabic + English support.
A collection of data analysis notebooks exploring data cleaning, preprocessing, and machine learning using Python, Pandas, and Scikit-Learn.
Machine learning regression project for predicting house prices using feature normalization, EDA, and model training with Scikit-learn.
A multimodal, context-aware health intelligence system that uses camera-based PPG, voice analysis, facial expression tracking, and environmental context to deliver real-time risk assessments.
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