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The Pragmatic Programmer for Machine Learning by Marco Scutari
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The Pragmatic Programmer for Machine Learning

Engineering Analytics and Data Science Solutions
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Description

Machine learning has redefined the way we work with data and is increasingly becoming an indispensable part of everyday life. The Pragmatic Programmer for Machine Learning: Engineering Analytics and Data Science Solutions discusses how modern software engineering practices are part of this revolution both conceptually and in practical applictions. Comprising a broad 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 engineering can be adapted to and integrated with the workflows of domain experts and probabilistic models. From choosing the right hardware to designing effective pipelines architectures and adopting software development best practices, this guide will appeal to machine learning and data science specialists, whilst also laying out key high-level principlesin a way that is approachable for students of computer science and aspiring programmers.

Author Biography:

Marco Scutari is a Senior Researcher 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 PhD 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 technologist based in Milan, Italy, with more than 15 years of experience in software engineering and IT operations in consulting and product companies as a CTO. His research focuses on software engineering, machine learning systems, embedded systems and cloud computing.
Release date Australia
April 1st, 2025
Audience
  • Professional & Vocational
Illustrations
3 Tables, black and white; 32 Line drawings, black and white; 32 Illustrations, black and white
Pages
340
ISBN-13
9780367255060
Product ID
36013763

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