- Performed EDA and feature engineering on flight dataset consisting of 5.8 million records
- Developed classification and regression models to predict flight delays and cancellations using pyspark pipelines
- Trained logistic regression, Random Forest using Pyspark ML
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Performed EDA and feature engineering on flight dataset consisting of 5.8 million records. Developed classification and regression models to predict flight delays and cancellations from various features by building PySpark pipelines.
surjits254/Flights-Delay-Cancellation-Prediction
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Performed EDA and feature engineering on flight dataset consisting of 5.8 million records. Developed classification and regression models to predict flight delays and cancellations from various features by building PySpark pipelines.
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