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Effective Machine Learning Teams

Best Practices for ML Practitioners

Gain the valuable skills and techniques you need to accelerate the delivery of machine learning solutions. With this practical guide, data scientists and ML engineers will learn how to bridge the gap between data science and Lean software delivery in a practical and simple way. Les mer

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Gain the valuable skills and techniques you need to accelerate the delivery of machine learning solutions. With this practical guide, data scientists and ML engineers will learn how to bridge the gap between data science and Lean software delivery in a practical and simple way. David Tan and Ada Leung from Thoughtworks show you how to apply time-tested software engineering skills and Lean delivery practices that will improve your effectiveness in ML projects.

Based on the authors' experience across multiple real-world data and ML projects, the proven techniques in this book will help teams avoid common traps in the ML world, so you can iterate more quickly and reliably. With these techniques, data scientists and ML engineers can overcome friction and experience flow when delivering machine learning solutions.

This book shows you how to:

Apply engineering practices such as writing automated tests, containerizing development environments, and refactoring problematic code bases
Apply MLOps and CI/CD practices to accelerate experimentation cycles and improve reliability of ML solutions
Design maintainable and evolvable ML solutions that allow you to respond to changes in an agile fashion
Apply delivery and product practices to iteratively improve your odds of building the right product for your users
Use intelligent code editor features to code more effectively

Detaljer

Forlag
O'Reilly Media
Innbinding
Paperback
Språk
Engelsk
ISBN
9781098144630
Utgivelsesår
2024
Format
23 x 18 cm

Om forfatteren

David Tan is a Senior ML Engineer at Thoughtworks. He has worked on multiple data and machine learning projects and applied time-tested software engineering practices to help teams iterate more quickly and reliably in the machine learning development lifecycle. Ada Leung is a Senior Business Analyst at Thoughtworks. She has technology delivery experience across several industries and her experience includes breaking down complex problems in varying domains, including customer facing applications, scaling of ML solutions, and more recently, data strategy and delivery of data platforms. She has been part of exemplar cross-functional delivery teams, both in-person and remotely, and is an advocate of cultivation as a way to build high performing teams. David "Dave" Colls is a technology leader with broad experience helping software and data teams deliver great results. David's technical background is in engineering design, simulation, optimization, and large-scale data-processing software. At Thoughtworks, he has led numerous agile and lean transformation projects, and most recently he established the Data and AI practice in Australia. In his practice leadership role, he develops new ML services, consults on ML strategy, and provides leadership to the delivery of ML initiatives.

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