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just clean up the readme a bit, after a quite
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README.md

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# Introduction
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QoA4ML consists of a set of utilities and specs for supporting quality of analytics in ML and data intensive (micro)services. Especially, we focus on services and systems of services across edge-cloud continuum, which are built as a composition of (micro)services.
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QoA4ML consists of a set of measurement probes, utilities and specs for supporting quality of analytics in ML and data intensive (micro)services. Especially, we focus on services and systems of services across edge-cloud continuum, which are built as a composition of (micro)services.
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## QoA4ML Specification
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The design of QoA4ML specification is in [language](language/)
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## QoA4ML Utilities
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## QoA4ML Probes
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Developers can call many functions from a QoAClient and QoA4ML's [utilities](qoa4ml_lib/utils.py) to evaluate/report ML-specific attributes (e.g., data quality, inference performance), build the quality reports, and send them to the observation services.
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The QoAClient can be initiated with various configurations for specifying observation server and communication protocols (e.g., messaging) in different formats (e.g., json and yaml).
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The detail documents for QoA4ML utilization is presented in [qoa4ml_lib](qoa4ml_lib/)
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We include [different probes](src/qoa4ml/probes/) for measuring quality of data, computing resource performance, etc.
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> For a local build and use QoA4ML one can do:
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##
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```bash
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$python3 -m pip install build
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$cd qoa4ml_lib/
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$python -m build
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```
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Developers can call many functions from a [QoAClient](src/qoa4ml/qoa_client.py) and QoA4ML's [utilities](src/qoa4ml/utils) to evaluate/report ML-specific attributes (e.g., data quality, inference performance), build the quality reports, and send them to the observation services.
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The QoAClient can be initiated with various configurations for specifying observation server and communication protocols (e.g., messaging) in different formats (e.g., json and yaml).
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## QoA4ML Reports
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