The code implements a precise anomaly detection system for structured transactional data using Python, TensorFlow, and Streamlit. It seamlessly integrates with SQL databases, preprocesses data, trains an autoencoder model, detects anomalies, and visualizes results. With customizable parameters and interactive features, it offers a versatile solution applicable across various domains.
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A sophisticated platform for anomaly detection in transaction data using autoencoders. Integrates SQL database connectivity, hyperparameter optimization, entropy analysis, and comprehensive visualizations. Tailored for financial fraud detection and industrial data analytics. (280 characters)
KarthikSundaram4419/AutoAnomalyDetect
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A sophisticated platform for anomaly detection in transaction data using autoencoders. Integrates SQL database connectivity, hyperparameter optimization, entropy analysis, and comprehensive visualizations. Tailored for financial fraud detection and industrial data analytics. (280 characters)
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