Timeseries Data: Deploy the model in the database
Dr. Julian Feinauer explains us how the AINode by Timecho works. It
is based on the open source project ApacheIoTDB.
42 Minuten
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vor 1 Jahr
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.
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.
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