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Add section to readme
Signed-off-by: Ryan Nett <[email protected]>
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README.md

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@@ -21,13 +21,18 @@ The following describes the layout of the repository and its different artifacts
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* `tensorflow-core`
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* All artifacts that build up the core language bindings of TensorFlow for Java
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* Intended audience: projects that provide their own APIs or frameworks on top of
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TensorFlow and just want a thin layer to access the TensorFlow runtime from the JVM
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TensorFlow and just want a thin layer to access the TensorFlow runtime from the JVM
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* `tensorflow-core-kotlin`
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* Kotlin API bindings for `tensorflow-core`. These are thin wrappers around the core APIs
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to make them more idiomatic for use in Kotlin, such as using parameters with default values
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operation builders instead of an `Options` vararg.
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* `tensorflow-framework`
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* Primary API for building and training neural networks with TensorFlow
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* Intended audience: neural network developers
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* For more information: [tensorflow-framework/README.md](tensorflow-framework/README.md)
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* `ndarray`
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* Generic utility library for n-dimensional data I/O operations
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* Used by TensorFlow but does not depend on TensorFlow
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the conventions established on this page:
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* [Reducing the Number of Dependencies](https://github.com/bytedeco/javacpp-presets/wiki/Reducing-the-Number-of-Dependencies)
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### Kotlin API
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Since the Kotlin API is just a wrapper of the Java API, it uses the Java platform artifacts instead of providing its own.
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To use, follow the instructions above for the Java API, but add `tensorflow-core-kotlin-api`,
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replacing `tensorflow-core-api` if you have explicitly included it.
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### Snapshots
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Snapshots of TensorFlow Java artifacts are automatically distributed after each update in the code. To use them, you need

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