A web app for Flight Delay Prediction using Random Forest Classifier
1st place solution (grad division) in 2020 TAMIDS Data Science Competition
Airline Flight Delay Intelligence — 6.2M+ flights, 14 airlines, 628 airports, seasonal patterns, on-time performance, delay cause analysis | Python | Pandas | Matplotlib
Visualization of Flights Delays in the US
Presentation Link: https://www.youtube.com/watch?v=MNy65IYIx24&t=13s
ML model predicts total flight delays using real-world data (carrier, weather, airport, etc.) with Linear, RF & GB regressors. Includes feature engineering & model comparison.
Flight delay and connection risk analysis using EDA and machine learning, supporting the GateRunner concept.
End-to-end ML pipeline to predict flight departure delays (>=15 mins) using flight & weather data.
A complete ML pipeline for predicting flight delays, including EDA, feature engineering, modeling, SHAP analysis, and error analysis.
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.
End-to-end flight delay prediction system using GCP, BigQuery ML, and Looker Studio — trained on 745K flights with weather and spatio-temporal features.
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.
My Research Project on the prediction of Flight Delay due to Weather Conditions. Provided by Solarillion Foundation.
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