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Feature/feature store 1.0.4 (#393)
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‎ads/feature_store/docs/requirements.txt

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sphinx_code_tabs
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sphinx-autobuild
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sphinx-autorun
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oracle_ads
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oracle_ads==2.9.0rc0
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furo
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IPython
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pandoc

‎ads/feature_store/docs/source/ads.feature_store.query.rst

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ads.feature_store.query package
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===============================
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ads.feature_store.query package
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-------------------------------
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.. automodule:: ads.feature_store.query.filter
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:members:
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:undoc-members:
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.. automodule:: ads.feature_store.query.join
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.. automodule:: ads.feature_store.query.query
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‎ads/feature_store/docs/source/feature_group.rst

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The ``get_validation_output()`` method has the following optional parameter:
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- ``job_id: string``. ID of the feature group job.
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``get_validation_output().to_pandas()`` Outputs the validation results for each expectation as Pandas dataframe.
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.. image:: figures/validation_results.png

‎ads/feature_store/docs/source/feature_store.rst

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df = feature_store.sql(sql)
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Create an Entity
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=============
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Use the ``create_entity()`` method of the ``FeatureStore`` instance to create an ``Entity``.
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feature_store.create_entity(name="<ENTITY_NAME>")
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Create a Transformation
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=======================
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Transformations in a feature store are the operations and processes applied to raw data to create, modify, or derive new features for use as inputs for machine learning models. These transformations are necessary for improving the quality, relevance, and usefulness of features that then enhance the performance of models.
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You can call the ``create_transformation()`` method of the FeatureStore instance to create a ``Transformation``.
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‎ads/feature_store/docs/source/feature_store_class.rst

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feature_store package
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=====================
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Subpackages
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-----------
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.. toctree::
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:maxdepth: 4
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ads.feature_store.query
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Submodules
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----------
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ads.feature_store package
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-------------------------
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.. automodule:: ads.feature_store.dataset
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.. automodule:: ads.feature_store.dataset_job
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.. automodule:: ads.feature_store.entity
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.. automodule:: ads.feature_store.feature
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.. automodule:: ads.feature_store.feature_group
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.. automodule:: ads.feature_store.feature_group_expectation
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.. automodule:: ads.feature_store.feature_group_job
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.. automodule:: ads.feature_store.feature_option_details
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.. automodule:: ads.feature_store.feature_store
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.. automodule:: ads.feature_store.feature_store_registrar
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.. automodule:: ads.feature_store.input_feature_detail
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.. automodule:: ads.feature_store.model_details
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.. automodule:: ads.feature_store.statistics_config
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.. automodule:: ads.feature_store.transformation
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.. automodule:: ads.feature_store.validation_output
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‎ads/feature_store/docs/source/index.rst

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statistics
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feature_validation
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data_versioning
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:caption: Release notes:
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release_notes
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.. toctree::
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:hidden:
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:maxdepth: 5
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:caption: Classes:
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module
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License
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Copyright (c) 2020, 2022 Oracle and/or its affiliates. Licensed under the `Universal Permissive License v1.0 <https://oss.oracle.com/licenses/upl/>`_

‎ads/feature_store/docs/source/module.rst

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===================
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Class Documentation
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===================
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.. toctree::
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:maxdepth: 2
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feature_store_class
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ads.feature_store package
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=========================
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.. automodule:: ads.feature_store.feature_group
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.. automodule:: ads.feature_store.feature_group_job
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.. automodule:: ads.feature_store.dataset
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.. automodule:: ads.feature_store.transformation
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.. automodule:: ads.feature_store.statistics_config
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.. automodule:: ads.feature_store.input_feature_detail
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.. automodule:: ads.feature_store.feature_group_expectation
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‎ads/feature_store/docs/source/quickstart.rst

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odsc conda install -s fspyspark32_p38_cpu_v1
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.. seealso::

‎ads/feature_store/docs/source/release_notes.rst

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* [DOCS] Updated terraform default version as 1.1.x
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‎ads/feature_store/docs/source/terraform.rst

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Terraform: Setting Up a Feature Store
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The following shows a terraform stack deployment of the feature store resources.
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Feature store requires the following policy statements to deploy the feature store in a Terraform stack:
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User VCN Deployment
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Specify the following details to onboard database instancesL
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