Machine learning system design interviews present some of the most challenging technical questions encountered in the field.这是Alex Xu和教授的第三本书,但它略有不同,因为它专注于ML设计。机器学习系统设计面试介绍了该领域遇到的一些最具挑战性的技术问题。 This comprehensive book offers a dependable ...
出版社:ByeByteGo 出版年:2023-1 页数:294 装帧:平装 ISBN:9781736049129 豆瓣评分 评价人数不足 评价: 写笔记 写书评 加入购书单 分享到 推荐 内容简介· ··· Machine learning system design interviews are the most difficult to tackle of all technical interview questions. This book provides a reliable...
—Boris Tseytlin, Senior Machine Learning Engineer, Planet Farms In the book you’ll follow two example companies each building a new ML system, exploring how their needs are expressed in design documents and learning best practices by writing your own. Along the way, you’ll learn how to ...
Machine Learning System Design With End-To-End Examples is a comprehensive step-by-step guide designed to help you work on your ML system at every stage of its creation—from information gathering and preliminary steps to implementation, release, and ongoing maintenance. The book is dedicated to...
This booklet covers four main steps of designing a machine learning system: Project setup Data pipeline Modeling: selecting, training, and debugging Serving: testing, deploying, and maintaining It comes with links to practical resources that explain each aspect in more details. It also suggests case...
Machine Learning Systems Design Chip Huyen huyenchip.com @chipro Table of Contents Next: Introduction
5. System Design Interview Author:Alex Xu Link:System Design Interview Finally, system design is an important part of job interviews at the top tech companies including MAANG. This book by Google engineer Alex Xu is a popular interview preparation material that covers a wide range of topics. It...
Pros: Ensures that machine learning outputs align with business requirements and constraints. This helps improve system reliability, safety, and usability. Cons: If managed poorly, can lead to a byzantine web of interacting rules that override each other in unexpected ways. May also encourage the ...
The objective of this book is to bring together a comprehensive collection of research trends on the edge field of Smart Systems, connecting Artificial Intelligence, Machine Learning, Computer Vision, Sensors Network, and Smart Tourism, from a set of international experts on the theory, design, eva...
It is then possible to create a training dataset for the machine learning system consisting of the complete input space and calculate the labels using the physical model. Figure 4-2. One situation when it is acceptable to overfit is when the entire domain space of observations can be tabulated...