⚽ A machine learning project that predicts the 2026 FIFA World Cup using FIFA rankings, historical match results, Poisson regression, and Monte Carlo simulation.

An AI-driven healthcare tool that predicts early symptoms of diseases based on user input. Uses ML classification on patient data and symptom patterns for prediction and prevention suggestions.

Simple IA de détection de spam

End-to-End MLOps Pipeline: Train, track, containerize, and deploy ML models via FastAPI REST API with automated CI/CD on Render.

ChurnSense-AI: End-to-end telecom churn prediction system with XGBoost, SHAP explainability, SQL analytics, Power BI dashboards, and customer risk intelligence.

An end-to-end Machine Learning application that predicts the likelihood of heart disease based on patient medical attributes. The project demonstrates the complete ML workflow, including data preprocessing, exploratory data analysis, model training, evaluation, and deployment through a user-friendly Flask web application.

End-to-end ML project that classifies emails as Spam or Not Spam using NLP, TF-IDF, Logistic Regression and Streamlit.

A deep learning project that predicts a student's **chance of admission** to a graduate program based on academic and profile features.

AI-powered IPL analytics platform with match prediction, team/player insights, and Explainable AI (XAI) — built with Flask, scikit-learn & Plotly.

Fine-tuned DistilBERT for political misinformation classification with cross-dataset evaluation across LIAR and Fakeddit benchmarks, compared against Logistic Regression, Naive Bayes, and SVM baselines.

Machine Learning project for predicting customer purchase behavior using a Decision Tree Classifier on the Bank Marketing Dataset with data preprocessing, feature importance analysis, confusion matrix visualization, and decision tree interpretation.

Python-based sales analytics project that transforms raw sales data into actionable business insights through data cleaning, KPI analysis, and interactive visualizations.

A complete financial data analytics project leveraging Python, SQL, Power BI, and machine learning for stock analysis, portfolio optimization, risk assessment, and time-series forecasting.

ML-based web app predicting diabetes, heart disease & Parkinson's using SVM, Logistic Regression & Random Forest

Java program that plots random points in a 3D space and assigns their (x, y, z) coordinates their respective [R, G, B] values and displays them in the plot with their RGB color.