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Updated a somewhat confusing heading in the Core APIs overview, and made a few copyedits.
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site/en/guide/core/index.md

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# TensorFlow Core APIs overview
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The TensorFlow Core APIs provide a set of comprehensive, composable, and
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extensible low-level APIs for high-performance (distributed & accelerated)
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extensible low-level APIs for high-performance (distributed and accelerated)
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computation, primarily aimed at building machine learning (ML) models as well as
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authoring ML workflow tools and frameworks within the TensorFlow platform. These
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APIs provide a foundation for creating highly configurable models with
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fine-grain control and new frameworks from the ground up.
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fine-grained control and new frameworks from the ground up.
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The Core APIs can be used as an alternative to high-level machine learning APIs
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like Keras. These high-level APIs are best suited for general machine learning
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needs. They offer a variety of modules that abstract away the complexities of ML
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while also offering functionalities for customization through subclassing. If
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you are looking for an overview of TensorFlow using Keras, see the Quickstarts
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and Keras sections in the [tutorials](https://www.tensorflow.org/tutorials)
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and Keras sections in the [tutorials](https://www.tensorflow.org/tutorials).
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## Core API developer audience
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## Who should use the Core APIs
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The TensorFlow Core low-level APIs are designed with the following ML Developers
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The TensorFlow Core low-level APIs are designed with the following ML developers
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in mind:
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* Researchers building complex models with high levels of configurability
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## Next steps
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The *Build with Core* documentation provides tutorials of basic machine learning
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concepts from scratch. These tutorials in this section help you get comfortable
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concepts from scratch. The tutorials in this section help you get comfortable
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with writing low-level code with Core APIs that you can then apply to more
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complex use cases of your own.
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