Published on April 21, 2018 by

In this episode of TensorFlow Meets, Laurence Moroney sits down with Derek Murray to discuss the latest on tf.data. Together, they discuss the impact of building fast, flexible, & efficient input pipelines with the tf.data API. Derek also touches on tf.data achieving performance benchmarks, the addition of convenient functions to make it easier for the TensorFlow community to get started, and datasets auto-tuning. Let us know what you think in the comments below!

tf.data Performance Guide → https://goo.gl/JASQ6Y
Derek’s tf.data talk at #TFDevSummit → https://goo.gl/mGMm7Q
Kaggle Datasets → https://goo.gl/SVmpT1

TensorFlow Meets Playlist → https://goo.gl/DTNXjd
Subscribe to the TensorFlow channel here → https://goo.gl/ht3WGe

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