platforms/core-execution/build-cache-http/                  @gradle/bt-cortex @gradle/dv-integrations-team
platforms/core-execution/build-cache-packaging/             @gradle/bt-cortex @gradle/dv-integrations-team
platforms/core-execution/build-cache-spi/                   @gradle/bt-cortex @gradle/dv-integrations-team
platforms/core-execution/hashing/                           @gradle/bt-cortex @gradle/dv-integrations-team

just getting started, GitHub has a
[how-to](https://help.github.com/articles/using-pull-requests/).

TensorFlow team members will be assigned to review your pull requests. Once the
pull requests are approved and pass continuous integration checks, a TensorFlow
team member will apply `ready to pull` label to your change. This means we are
working on getting your pull request submitted to our internal repository. After

researchers push the state-of-the-art in ML and developers easily build and
deploy ML-powered applications.

TensorFlow was originally developed by researchers and engineers working within
the Machine Intelligence team at Google Brain to conduct research in machine
learning and neural networks. However, the framework is versatile enough to be
used in other areas as well.