ML data labeling autonomous agent
Streamlit
Problem statement: Audit of IoT data from sensors becomes increasingly more difficult due to complex rules, which need to be applied in the observability tools. Why: Number of sensors increased and complexity of understanding metrics is requires machine learning solutions. However, in order to build machine learning based observability models we need labeled data for specific domain behaviors. These rules are understood as anomalies by domain experts (Predictive maintenance). Solution: We would like to create tool to support domain experts.So that they can easily find anomalies in the data for preventing issues of machines malfunctions.
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