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https://github.com/2003harsh/emotion-detection-using-mlops

This Python-based sentiment analysis project emphasizes MLOps practices. It features data ingestion, preprocessing, and Bag of Words (BOW) for feature engineering. DVC is used for version control, while an ML pipeline manages the workflow for training a Gradient Boosting Classifier. Model performance is evaluated using metrics like accuracy and ROC
https://github.com/2003harsh/emotion-detection-using-mlops

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This Python-based sentiment analysis project emphasizes MLOps practices. It features data ingestion, preprocessing, and Bag of Words (BOW) for feature engineering. DVC is used for version control, while an ML pipeline manages the workflow for training a Gradient Boosting Classifier. Model performance is evaluated using metrics like accuracy and ROC

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