Explore live open-source projects and AI models.

Crypto & Stock* price prediction with regression models.

Harness the power of machine learning to forecast rice and wheat crop yields per acre in India, aiming to empower smallholder farmers, combat poverty and malnutrition, utilizing data from Digital Green surveys to revolutionize agriculture and promote sustainable practices in the face of climate c... Read more

Architected a high-performance predictive pipeline processing 15 Million transactions. Optimized memory by 70% via custom downcasting and implemented Tweedie-LightGBM to solve zero-inflation in retail demand. Delivered a 28-day future forecast for Walmart inventory with high-precision RMSE of 2.20.

Machine Learning Models Deployment using C++ Code Generation

Autonomous prediction-market trading bot: ML ensemble + LLM signals, real-time WebSocket alerts

Python libraries like Scikit-learn, TensorFlow, Keras, and PyTorch are used for machine learning and deep learning. XGBoost and LightGBM specialize in boosting models, while Pandas and NumPy handle data, and Matplotlib and Seaborn provide visualization tools.

Fork of Microsoft/LightGBM to include support for the CEGB (Cost Efficient Gradient Boosting) algorithm. Original repository at https://github.com/Microsoft/LightGBM

focal loss (multi-class) for lightgbm/xgboost

Tree species classification using LightGBM in the context of project TreeSatAI

Solution to KDD Cup 2019 ML competition using LightGBM and Deep FM