Build a Machine Learning Platform (from Scratch)
商品資訊
ISBN13：9781633437333
出版社：MANNING PUBN
作者：Benjamin Tan Wei Hao
出版日：2025/11/25
裝訂：平裝
定價
：NT$ 3000 元無庫存，下單後進貨(到貨天數約30-45天)
下單可得紅利積點：90 點
商品簡介
商品簡介
Get your machine learning models out of the lab and into production! Delivering a successful machine learning project is hard. Build a Machine Learning Platform (From Scratch) makes it easier. In it, you'll design a reliable ML system from the ground up, incorporating MLOps and DevOps along with a stack of proven infrastructure tools including Kubeflow, MLFlow, BentoML, Evidently, and Feast. In Build a Machine Learning Platform (From Scratch) you'll learn how to: - Set up an MLOps platform
- Deploy machine learning models to production
- Build end-to-end data pipelines
- Effective monitoring and explainability A properly designed machine learning system streamlines data workflows, improves collaboration between data and operations teams, and provides much-needed structure for both training and deployment. In Build a Machine Learning Platform (From Scratch) you'll learn how to design and implement a machine learning system from the ground up. You'll appreciate this instantly-useful introduction to achieving the full benefits of automated ML infrastructure. About the book Build a Machine Learning Platform (From Scratch) teaches you to set up and run a production-quality machine learning system using open source tools. Chapter-by-chapter, you'll assemble a delivery pipeline for an image classifier and a recommendation system, learning best practices as you go. You'll get hands-on experience with the most important parts of the machine learning workflow, including orchestrating pipelines; model training, inference, and serving; and monitoring and explainability. Soon, you'll be deploying models that are fast to production and easy to maintain and scale. About the reader For data scientists or software engineers who know how to program in Python. About the author Benjamin Tan is a product manager and principal engineer for sata Science at DKatalis where he leads a team of talented machine learning engineers, data scientists, and data engineers. He is also the author of The Little Elixir and OTP Guidebook and Building an ML Pipeline with Kubeflow (liveProject) from Manning, and Mastering Ruby Closures. Shanoop Padmanabhan is a software engineering manager at Continental Automotive, where he leads a team of software engineers focusing on machine learning based perception for autonomous vehicles. Varun Mallya is a machine learning engineer working at DKatalis where he is responsible for the setup and maintenance of the Bank's machine learning platform. Get a free eBook (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.
- Deploy machine learning models to production
- Build end-to-end data pipelines
- Effective monitoring and explainability A properly designed machine learning system streamlines data workflows, improves collaboration between data and operations teams, and provides much-needed structure for both training and deployment. In Build a Machine Learning Platform (From Scratch) you'll learn how to design and implement a machine learning system from the ground up. You'll appreciate this instantly-useful introduction to achieving the full benefits of automated ML infrastructure. About the book Build a Machine Learning Platform (From Scratch) teaches you to set up and run a production-quality machine learning system using open source tools. Chapter-by-chapter, you'll assemble a delivery pipeline for an image classifier and a recommendation system, learning best practices as you go. You'll get hands-on experience with the most important parts of the machine learning workflow, including orchestrating pipelines; model training, inference, and serving; and monitoring and explainability. Soon, you'll be deploying models that are fast to production and easy to maintain and scale. About the reader For data scientists or software engineers who know how to program in Python. About the author Benjamin Tan is a product manager and principal engineer for sata Science at DKatalis where he leads a team of talented machine learning engineers, data scientists, and data engineers. He is also the author of The Little Elixir and OTP Guidebook and Building an ML Pipeline with Kubeflow (liveProject) from Manning, and Mastering Ruby Closures. Shanoop Padmanabhan is a software engineering manager at Continental Automotive, where he leads a team of software engineers focusing on machine learning based perception for autonomous vehicles. Varun Mallya is a machine learning engineer working at DKatalis where he is responsible for the setup and maintenance of the Bank's machine learning platform. Get a free eBook (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.
購物須知
外文書商品之書封，為出版社提供之樣本。實際出貨商品，以出版社所提供之現有版本為主。部份書籍，因出版社供應狀況特殊，匯率將依實際狀況做調整。
無庫存之商品，在您完成訂單程序之後，將以空運的方式為你下單調貨。為了縮短等待的時間，建議您將外文書與其他商品分開下單，以獲得最快的取貨速度，平均調貨時間為1~2個月。
為了保護您的權益，「三民網路書店」提供會員七日商品鑑賞期(收到商品為起始日)。
若要辦理退貨，請在商品鑑賞期內寄回，且商品必須是全新狀態與完整包裝(商品、附件、發票、隨貨贈品等)否則恕不接受退貨。