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synth-data-metrics


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Author: K.Court
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Summary: Synthetic Data Metrics is a Python library for evaluating synthetic data quality across a wide range of data types (image, tabular, time series, language) and approaches to evaluation.
Latest version: 0.0.1
Required dependencies: absl-py | astunparse | cachetools | certifi | charset-normalizer | flatbuffers | gast | google-auth | google-auth-oauthlib | google-pasta | grpcio | h5py | idna | imageio | joblib | keras | libclang | markdown | markupsafe | matplotlib | networkx | numpy | oauthlib | opt-einsum | packaging | pandas | pillow | protobuf | pyasn1 | pyasn1-modules | python-dateutil | pytz | pywavelets | requests | requests-oauthlib | rsa | scikit-image | scikit-learn | scipy | six | tensorboard | tensorboard-data-server | tensorboard-plugin-wit | tensorflow | tensorflow-estimator | tensorflow-io-gcs-filesystem | termcolor | threadpoolctl | tifffile | typing-extensions | urllib3 | werkzeug | wrapt

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