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Developed a robust spam detection system on AWS using an ETL workflow with an EMR cluster (PySpark, Hive, Pig) for efficient data processing. Implemented TF-IDF counting for spam and ham classification. Utilized S3 for data storage, CloudWatch for monitoring, and Cloud9 as the collaborative IDE. Achieved streamlined and accurate classification of spam and ham accounts.
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