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Designing Data Pipelines with TensorFlow 2.0

This course will evaluate one of the largest changes from TensorFlow 1.0 to TensorFlow 2.0 – the tf.data module. This simplified and unified interface makes managing data pipelines easier with tf.data.

Chase DeHan - Pluralsight course - Designing Data Pipelines with TensorFlow 2.0
by Chase DeHan

What you'll learn

TensorFlow 2.0 has made it easier to manage data pipelines with tf.data through their simplified and unified interface. In this course, Designing Data Pipelines with TensorFlow 2.0, you’ll learn to leverage the performance improvements from the TensorFlow data module. First, you’ll discover how to load data into TensorFlow. Next, you’ll explore prepping data for model training and feature engineering. Finally, you’ll learn how to leverage the performance optimizations of the data pipeline. When you’re finished with this course, you’ll have the skills and knowledge of building data pipelines needed to have data ready for model training in TensorFlow.

Table of contents

About the author

Chase DeHan - Pluralsight course - Designing Data Pipelines with TensorFlow 2.0
Chase DeHan

Chase is currently Lead Data Scientist at Tesorio and formerly was an Assistant Professor of Finance and Economics at the University of South Carolina Upstate.

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