A web app for Flight Delay Prediction using Random Forest Classifier
1st place solution (grad division) in 2020 TAMIDS Data Science Competition
A complete ML pipeline for predicting flight delays, including EDA, feature engineering, modeling, SHAP analysis, and error analysis.
ML model predicts total flight delays using real-world data (carrier, weather, airport, etc.) with Linear, RF & GB regressors. Includes feature engineering & model comparison.
End-to-end ML pipeline to predict flight departure delays (>=15 mins) using flight & weather data.
A machine learning pipeline using PySpark to predict flight arrival delays based on departure delays, timing, and aircraft metadata from the 2007 US DOT dataset.
Visualization of Flights Delays in the US
Presentation Link: https://www.youtube.com/watch?v=MNy65IYIx24&t=13s
My Research Project on the prediction of Flight Delay due to Weather Conditions. Provided by Solarillion Foundation.
Intelligent platform for US flight delay prediction using XGBoost, SHAP explainability, K-Means clustering, and RAG with Qwen 3 (Hugging Face). Delivers explained recommendations via FastAPI + Dash dashboard.
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