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An end-to-end machine learning pipeline on Microsoft Azure to predict flight delays using historical flight and weather data. The project integrated Azure Blob Storage, Data Factory, and Databricks for data ingestion, processing, and analysis, and employed various ML algorithms for model training and evaluation and visualisation on Power BI
Submission for MapReduce code to find the most frequent traveller
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An end-to-end machine learning pipeline on Microsoft Azure to predict flight delays using historical flight and weather data. The project integrated Azure Blob Storage, Data Factory, and Databricks for data ingestion, processing, and analysis, and employed various ML algorithms for model training and evaluation and visualisation on Power BI