41 Min.

Timeseries Data: Deploy the model in the database Industrial AI Podcast

    • Technologie

AINode is the third internal node after ConfigNode and DataNode in Apache IoTDB. This node extends the capability of IoTDB to perform machine learning analysis on time series data by interacting with the DataNode and ConfigNode clusters. AINode allows the integration of existing machine learning models by registering them and executing time series analysis tasks through simple SQL statements on specified time series data. This seamlessly combines model creation, management, and inference within the database engine. The framework currently supports common machine learning algorithms or proprietary models for typical time series analysis scenarios like time series prediction and anomaly detection.

AINode is the third internal node after ConfigNode and DataNode in Apache IoTDB. This node extends the capability of IoTDB to perform machine learning analysis on time series data by interacting with the DataNode and ConfigNode clusters. AINode allows the integration of existing machine learning models by registering them and executing time series analysis tasks through simple SQL statements on specified time series data. This seamlessly combines model creation, management, and inference within the database engine. The framework currently supports common machine learning algorithms or proprietary models for typical time series analysis scenarios like time series prediction and anomaly detection.

41 Min.

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