Time Series

Time Series Analysis

Analyze data over time and find valuable patterns.

Analyzing recurrent events is one of the most fascinating objectives of Data Analytics. It has use cases in various domains, such as financial data, medical analysis or occupancy detection for rooms. However, in some of said domains, labeled training data to build recurring models is not available as needed. For instance, in occupancy detection, a label is needed to indicate if and how many people are in a certain room, which is not stored historically and this not available.

With kern, building such training data becomes much easier. By crafting information sources of various types (such as labeling functions analyzing windowed data slices, active learning models or crowdlabeling resources), your data can be labeled on large-scale while maintaining data quality.

If you’re interested in trying out kern for time series data, send us message or register for our free version. We’re happy to help along the way to build the ideal dataset for your needs!

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