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.
Author Name: Chase DeHan
Author Description:
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. He holds a BS, MS, and PhD, all in Economics, from the University of Utah. Prior to graduate school, Chase served two combat tours to Iraq with the US Marine Corps and competed in the 2010 Winter Olympic Trials in Bobsled. Chase is passionate about building automated machine learning systems and is a regular speaker at academic and pra… more

Table of Contents

• Course Overview
  1min
• Evaluating TensorFlow Capabilities
  15mins
• Loading Data in TensorFlow
  37mins
• Prepping Data
  33mins
• Optimizing Performance of Pipelines
  25mins