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Building Machine Learning Pipelines: Automating Model Life Cycles with Tensorflow Paperback – 28 July 2020

4.3 out of 5 stars 35 ratings

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Product description

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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Product details

  • Publisher ‏ : ‎ O'Reilly Media, Inc, USA (28 July 2020)
  • Language ‏ : ‎ English
  • Paperback ‏ : ‎ 366 pages
  • ISBN-10 ‏ : ‎ 1492053198
  • ISBN-13 ‏ : ‎ 978-1492053194
  • Dimensions ‏ : ‎ 17.78 x 1.93 x 23.34 cm
  • Customer Reviews:
    4.3 out of 5 stars 35 ratings

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Hannes is a Senior Machine Learning Engineer at SAP Concur where he focuses on ML Infrastructure and Natural Language Processing projects. Hannes is a Google Developer Expert for Machine Learning and a co-author of machine learning publications like NLP in Action

and the O'Reilly publication on Building Machine Learning Pipelines with TensorFlow.

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2.0 out of 5 stars Not worth the money. Good intro, but nothing more than the official manual
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