The Pragmatic Programmer for Machine Learning - Marco Scutari, Mauro Malvestio

The Pragmatic Programmer for Machine Learning

Engineering Analytics and Data Science Solutions
Buch | Hardcover
340 Seiten
2023
Chapman & Hall/CRC (Verlag)
978-0-367-26350-8 (ISBN)
93,50 inkl. MwSt
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.
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.

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.

Preface

1 What is This Book About?

2 Hardware Architectures

3 Variable Types and Data Structures

4 Analysis of Algorithms

5 Designing and Structuring Pipelines

6 Writing Machine Learning Code

7 Packaging and Deploying Pipelines

8 Documenting Pipelines

9 Troubleshooting and Testing Pipelines

10 Tools for Developing Pipelines

11 Tools to Manage Pipelines in Production

12 Recommending Recommendations: A Recommender

System Using Natural Language Understanding

Bibliography

Index

Erscheinungsdatum
Reihe/Serie Chapman & Hall/CRC Machine Learning & Pattern Recognition
Zusatzinfo 3 Tables, black and white; 32 Line drawings, black and white; 32 Illustrations, black and white
Sprache englisch
Maße 156 x 234 mm
Gewicht 800 g
Themenwelt Informatik Datenbanken Data Warehouse / Data Mining
Mathematik / Informatik Informatik Programmiersprachen / -werkzeuge
Mathematik / Informatik Informatik Software Entwicklung
ISBN-10 0-367-26350-5 / 0367263505
ISBN-13 978-0-367-26350-8 / 9780367263508
Zustand Neuware
Informationen gemäß Produktsicherheitsverordnung (GPSR)
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