Top 9% solution for the Kaggle March Machine Learning Mania 2026. Optimized ElasticNet, and HistGradientBoosting models blended with betting market insights.
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Updated
Apr 15, 2026 - Jupyter Notebook
Top 9% solution for the Kaggle March Machine Learning Mania 2026. Optimized ElasticNet, and HistGradientBoosting models blended with betting market insights.
Supervised surface-condition classification from torque-angle time series recorded by an automated screwdriving station.
Machine Learning project for predicting silica concentration in a mining flotation process using HistGradientBoostingRegressor.
Credit risk modeling with HistGradientBoosting, featuring evaluation, SHAP explainability, threshold optimization, and high-risk client analysis.
A machine learning web app that predicts a student’s expected score and grade using self-study hours, attendance, and class participation, also showing performance insights such as risk level, focus area, and improvement recommendations. It is built with React, FastAPI, and scikit-learn. Deployment: Vercel for frontend, Render for backend.
Network intrusion detection using NSL-KDD with binary attack detection, multiclass attack classification, and a live web traffic anomaly dashboard.
End-to-end real-time anomaly detection system leveraging Kafka streaming and stateful behavioural features for low-latency anomaly detection.
End-to-end fraud and AML analytics project using Python, PostgreSQL, machine learning and Power BI.
Intelligent Django weather forecasting application powered by Machine Learning, using OpenWeatherMap & Open-Meteo APIs to predict short-term rainfall from 365 days of historical weather data.
Comparative machine learning study for non-contact body temperature prediction using Infrared Thermography, featuring HGB, Random Forest, CatBoost, Lasso, LSTM, TOPSIS ranking, Radar Plot visualization, and LIME explainability.
Machine learning analysis of speed-dating response prediction using HistGradientBoosting and relationship-based feature engineering.
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