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Building Machine Learning Pipelines: Automating Model Life Cycles with
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Building Machine Learning Pipelines: Automating Model Life Cycles with Tensorflow Paperback - 2020

by Hannes Hapke; Catherine Nelson


Details

  • Title Building Machine Learning Pipelines: Automating Model Life Cycles with Tensorflow
  • Author Hannes Hapke; Catherine Nelson
  • Binding Paperback
  • Pages 364
  • Volumes 1
  • Language ENG
  • Publisher O'Reilly Media
  • Date 2020-08-18
  • Features Index
  • ISBN 9781492053194 / 1492053198
  • Weight 1.28 lbs (0.58 kg)
  • Dimensions 9.19 x 7 x 0.76 in (23.34 x 17.78 x 1.93 cm)
  • Library of Congress subjects Machine learning, Business enterprises - Data processing
  • Library of Congress Catalog Number 2022276253
  • Dewey Decimal Code 006.31

About the author

Hannes Hapke is a VP of Engineering at Caravel, a machine learning company providing novel personalization products for the retail industry. Prior to joining Caravel, Hannes was a Ssenior data science engineer at Cambia Health Solutions, a health solutions provider for 2.6 million people and a machine learning engineer at Talentpair, Inc., where he developed novel deep learning model for recruiting companies. Hannes cofounded a renewable energy startup which applied deep learning to detect homes would be optimal candidates for solar power.Additionally, Hannes has coauthored a publication about natural language processing and deep learning and presented at various conferences about deep learning and Python.

Catherine Nelson is a senior data scientist for Concur Labs at SAP Concur, where she explores innovative ways to use machine learning to improve the experience of a business traveller. She is particularly interested in privacy-preserving ML and applying deep learning to enterprise data. In her previous career as a geophysicist she studied ancient volcanoes and explored for oil in Greenland. Catherine has a PhD in geophysics from Durham University and a Masters of Earth Sciences from Oxford University.

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