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. The Pragmatic Programmer for Ma-chine Learning: Engineering Analytics and Data Science Solutions 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.