very differently from normal language bindings.
First-class language and compiler support allow us to innovate in areas that
-traditionally were out of bounds for machine learning libraries. Our programming
-model combines the performance of TensorFlow graphs with the flexibility and
-expressivity of Eager execution, while keeping a strong focus on improved
-usability at every level of the stack.
-
+traditionally were out of bounds for machine learning libraries. Our
+programming model combines the performance of TensorFlow graphs with the
+flexibility and expressivity of Eager execution, while keeping a strong focus
+on improved usability at every level of the stack.
## Open Source
We have released Swift for TensorFlow as an open-source project on GitHub!
-Our [central repository](https://github.com/tensorflow/swift) contains project
-documentation, including an
-[overview and technical papers](https://github.com/tensorflow/swift/tree/master/docs)
-explaining specific areas of the project in depth. This repo also includes
-instructions for [installing prebuilt packages](https://github.com/tensorflow/swift/blob/master/Installation.md)
-for macOS and Linux platforms, [simple usage instructions](https://github.com/tensorflow/swift/blob/master/Usage.md),
-and how to build from source.
+Our [documentation repository](https://github.com/tensorflow/swift) contains a
+[project overview](https://github.com/tensorflow/swift/blob/master/docs/DesignOverview.md)
+and [technical papers](https://github.com/tensorflow/swift/tree/master/docs)
+explaining specific areas in depth. There are also instructions for [installing
+pre-built packages](https://github.com/tensorflow/swift/blob/master/Installation.md)
+(for macOS and Ubuntu) as well as a simple
+[usage tutorial](https://github.com/tensorflow/swift/blob/master/Usage.md).
Moving forward, we will use an open design model and all discussions will be
public.