TensorFlow was recently released to the open source world as a platform for developing cutting-edge ML models, with an emphasis on deep architectures including neural nets, convolutional neural nets, recurrent neural nets, and LSTM's. The open source version of TensorFlow now supports distributed computation across many machines, opening up a new level of scale to the research community. In this talk, we'll go over a quick introduction to the basic TensorFlow abstractions, and will also look at some higher-level API's that offer a convenient level of abstraction for many common use cases. Folks interested in learning more are encouraged to visit tensorflow.org, and the excellent Udacity course on ML featuring TensorFlow.