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TensorFlow Probability: Learning with confidence (TF Dev Summit '19)

TensorFlow Probability (TFP) is a Python library built on TensorFlow that makes it easy to combine probabilistic models and deep learning on modern hardware (TPU, GPU). It's for data scientists, statisticians, and ML researchers/practitioners who want to encode domain knowledge to understand data and make predictions with uncertainty estimates. In this talk we focus on the "layers" module and demonstrate how TFP "distributions" fit naturally with Keras to enable estimating aleatoric and/or epistemic uncertainty. See the revamped dev site → https://www.tensorflow.org/ Watch all TensorFlow Dev Summit '19 sessions → http://bit.ly/TFDS19Sessions Event homepage → http://bit.ly/TFDS19 Subscribe to the TensorFlow YouTube channel → https://bit.ly/TensorFlow1 Speaker: Josh Dillon, Software Engineer Music by Terra Monk → http://bit.ly/TerraMonkTFDS Event Photo Album → http://bit.ly/TFSummit19 event: TensorFlow Dev Summit 2019; re_ty: Publish; product: TensorFlow - TensorFlow Probability; fullname: Josh Dillon;