CNN-Based-Anomaly-Detection-in-Time-Series-Data
PublicThis project demonstrates how to build a Convolutional Neural Network (CNN) model for anomaly detection in time series data using Keras. It is implemented in Google Colab and uses a CSV dataset containing time series values. The model detects anomalies based on reconstruction errors by setting a dynamic threshold.
Creat：2024-10-24T12:49:29
Update：2024-12-19T13:35:00
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