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The Pragmatic Programmer for Machine Learning

The Pragmatic Programmer for Machine Learning


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About the Book

Machine learning has redefined the way we work with data and is increasingly becoming an indispensable part of everyday life, yet software engineering has played a remarkably small role compared to other disciplines. This book addresses such a disparity.

Comprising a complete overview of how to design machine learning pipelines as well as the state-of-the-art tools we use to make them, this book provides a multi-disciplinary view of how traditional software learning practices can be integrated with the workflows of domain experts.

From choosing the right hardware to analysing algorithms and designing scalable architectures, this guide to software engineering will appeal to machine learning and data science specialists, whilst also utilising natural language and clear case studies to be accessible for students of computer science and aspiring programmers.

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About the Author:

Marco Scutari is a Senior Lecturer at Istituto Dalle Molle di Studi
sull'Intelligenza Artificiale (IDSIA), Switzerland. He has held positions in
Statistics, Statistical Genetics and Machine Learning in the UK and Switzerland
since completing his Ph.D. in Statistics in 2011. His research focuses on the
theory of Bayesian networks and their applications to biological and clinical
data, as well as statistical computing and software engineering.

Mauro Malvestio is a Senior Software Development Consultant at Vipera, with more than
15 years of experience in software engineering and IT operations in consulting
and product companies as CTO. His research focuses on software engineering,
machine learning systems, embedded system and cloud computing.


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Product Details
  • ISBN-13: 9780367263508
  • Publisher: CRC Press
  • Publisher Imprint: Crc Press
  • Height: 233 mm
  • No of Pages: 336
  • Series Title: Chapman & Hall/CRC Machine Learning & Pattern Recognition
  • Sub Title: Engineering Analytics and Data Science Solutions
  • Width: 156 mm
  • ISBN-10: 0367263505
  • Publisher Date: 31 Mar 2023
  • Binding: Hardback
  • Language: English
  • Returnable: N
  • Spine Width: 0 mm
  • Weight: 692 gr


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