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docs/source/user_guide/model_training/automl/index.rst

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.. note::
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The ADS `AutoML <https://accelerated-data-science.readthedocs.io/en/v2.8.1/ads.automl.html#module-ads.automl.driver>`__, `AutoMLProvider <https://accelerated-data-science.readthedocs.io/en/v2.8.1/ads.automl.html#ads.automl.provider.AutoMLProvider>`__, `MLXGlobalExplainer <https://accelerated-data-science.readthedocs.io/en/v2.8.1/ads.explanations.html>`, `MLXLocalExplainer <https://accelerated-data-science.readthedocs.io/en/v2.8.1/ads.explanations.html>`__ and `MLXWhatIfExplainer <https://accelerated-data-science.readthedocs.io/en/v2.8.1/ads.explanations.html>`__, `AutoMLModel <https://accelerated-data-science.readthedocs.io/en/v2.8.1/ads.explanations.html>`__, `AutoMLExtractor <https://accelerated-data-science.readthedocs.io/en/v2.8.1/ads.explanations.html>`__ are deprecated in 2.8.2 and will be removed in 3.0.0. This is to in favor of working directly with Oracle AutoMLx library.
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The ADS `AutoML <https://accelerated-data-science.readthedocs.io/en/v2.8.1/ads.automl.html#module-ads.automl.driver>`__, `AutoMLProvider <https://accelerated-data-science.readthedocs.io/en/v2.8.1/ads.automl.html#ads.automl.provider.AutoMLProvider>`__, `MLXGlobalExplainer <https://accelerated-data-science.readthedocs.io/en/v2.8.1/ads.explanations.html>`__, `MLXLocalExplainer <https://accelerated-data-science.readthedocs.io/en/v2.8.1/ads.explanations.html>`__ and `MLXWhatIfExplainer <https://accelerated-data-science.readthedocs.io/en/v2.8.1/ads.explanations.html>`__, `AutoMLModel <https://accelerated-data-science.readthedocs.io/en/v2.8.1/ads.explanations.html>`__, `AutoMLExtractor <https://accelerated-data-science.readthedocs.io/en/v2.8.1/ads.explanations.html>`__ are deprecated in 2.8.2 and will be removed in 3.0.0. This is to in favor of working directly with Oracle AutoMLx library.
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With AutoMLx moving into the open source domain, working directly with the library has many benefits.
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One of these is that ADS and AutoMLx can now have independent version cadences.
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AutoMLx is under active development, and will be expanding into areas of explainability, fairness and deep learning.

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