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medAli-ai / Beijing-air-quality-prediction-internship

This project has applied Machine Learning and Deep Learning techniques to analyse and predict the Air Quality in Beijing.

deep-learning time-series gpu machine-learning-algorithms transformers cnn pytorch lstm feature-engineering tabnet air-quality-prediction xgbbost

Updated Sep 19, 2022
Jupyter Notebook

Shadin710 / Energy-Demand-Prediction

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A machine learning project that forecasts electricity demand using time-series energy market data. It applies feature engineering techniques such as lag features, rolling statistics, and time-based variables, and uses an XGBoost regression model to predict short-term demand for infrastructure planning and analysis.

python numpy integration-testing scikit-learn pandas joblib streamlit xgbbost

Updated Jun 20, 2026
Python

anandrai15 / Volatility-Forecasting-and-Regime-Aware-Risk-Modeling-using-XGBoost

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A quant research project that forecasts short-term market volatility using time-series features, XGBoost, shock detection, and regime-aware signals. The model is then used for risk-based position sizing to evaluate whether volatility forecasts can improve portfolio stability.

python machine-learning forecasting quantitative-finance volatility risk-management risk-modelling volatility-modeling forecasting-time-series xgbbost

Updated May 27, 2026
Python

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