title: Building Machine Learning Projects with TensorFlow
author:  Rodolfo Bonnin 
description: Rodolfo Bonnin is a systems engineer and PhD student at Universidad Tecnologica Nacional, Argentina. He also pursued parallel programming and image understanding postgraduate courses at Uni Stuttgart, Germany. He has done research on high performance computing since 2005 and began studying and implementing convolutional neural networks in 2008,writing a CPU and GPU - supporting neural network feed forward stage. More recently he's been working in the field of fraud pattern detection with Neural Networks, and is currently working on signal classification using ML techniques.
zlib_text: **Praise for** _ **Building Machine Learning Pipelines**_
  
  >  _“I wish this book had existed when I started working in production ML!
  > It’s an outstanding resource for getting a comprehensive view of production
  > ML systems in general, and TFX in particular. Hannes and Catherine have
  > worked directly with the TensorFlow team to get the most accurate
  > information available for including in this book, and then explained it in
  > clear, concise explanations and examples.”_
  
  > Robert Crowe, TensorFlow Developer Advocate, Google
  
  >  _“The data science practitioner knows that real-world machine learning
  > involves more than just machine learning model training. This book
  > demystifies the hidden technical debt in modern machine learning workflows
  > such that you can put the lab and factory data science patterns into
  > production as repeatable workflows.”_
  
  > Josh Patterson, CEO, Patterson Consulting, Coauthor of Deep Learning: A
  > Practitioner’s Approach  
  >  and Kubeflow Operations Guide
  