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Design systems optimized for deep learning models. Written for software engineers, this book teaches you how to implement a maintainable platform for developing deep learning models.
Engineering Deep Learning Systems is a practical guide for software engineers and data scientists who are designing and building platforms for deep learning. It’s full of hands-on examples that will help you transfer your software development skills to implementing deep learning platforms.
In Engineering Deep Learning Systems, you’ll learn how to build automated and scalable services for core tasks like dataset management, model training/serving, and hyperparameter tuning. This book is the perfect way to step into an exciting—and lucrative—career as a deep learning engineer.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
Designing Deep Learning Systems
by Chi Wang; Donald SzetoFormat: Bound Book
Pub. Date: 2023-09-19
Publisher(s): Simon & Schuster
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Summary
Author Biography
Chi Wang is a principal software developer in the Salesforce Einstein group where he builds the deep learning platform for millions of Salesforce customers. Previously, he worked at Microsoft Bing and Azure on building large-scale distributed systems. Chi has filed six patents, mostly in deep learning systems.
Donald Szeto was the co-founder and CTO of PredictionIO, a startup that aimed to help democratize and accelerate the adoption of machine learning. PredictionIO was acquired by Salesforce, where he continued his work on machine learning and deep learning systems. Donald is currently investing in, advising, and mentoring technology startups.
Donald Szeto was the co-founder and CTO of PredictionIO, a startup that aimed to help democratize and accelerate the adoption of machine learning. PredictionIO was acquired by Salesforce, where he continued his work on machine learning and deep learning systems. Donald is currently investing in, advising, and mentoring technology startups.
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