Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications

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Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications

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內容描述

Many tutorials show you how to develop ML systems from ideation to deployed models. But with constant changes in tooling, those systems can quickly become outdated. Without an intentional design to hold the components together, these systems will become a technical liability, prone to errors and be quick to fall apart.
In this book, Chip Huyen provides a framework for designing real-world ML systems that are quick to deploy, reliable, scalable, and iterative. These systems have the capacity to learn from new data, improve on past mistakes, and adapt to changing requirements and environments. Youà Ã?Â[ ll learn everything from project scoping, data management, model development, deployment, and infrastructure to team structure and business analysis.

Learn the challenges and requirements of an ML system in production
Build training data with different sampling and labeling methods
Leverage best techniques to engineer features for your ML models to avoid data leakage
Select, develop, debug, and evaluate ML models that are best suit for your tasks
Deploy different types of ML systems for different hardware
Explore major infrastructural choices and hardware designs
Understand the human side of ML, including integrating ML into business, user experience, and team structure

作者介紹

Chip Huyen (https: //huyenchip.com) is an engineer and founder who develops infrastructure for real-time machine learning. Through her work at Netflix, NVIDIA, Snorkel AI, and her current startup, she has helped some of the world's largest organizations develop and deploy machine learning systems. She is the founder of a startup that focuses on real-time machine learning.

In 2017, she created and taught the Stanford course TensorFlow for Deep Learning Research. She is currently teaching CS 329S: Machine Learning Systems Design at Stanford. This book is based on the course's lecture notes.

She is also the author of four Vietnamese books that have sold more than 100,000 copies. The first two books belong to the series Xach ba lo len va Di (Quang Van 2012, 2013). The first book in the series was the #1 best-selling book of 2012 on Tiki.vn. The series was among FAHASA's Top 10 Readers Choice Books in 2014.

Chip's expertise is in the intersection of software engineering and machine learning. LinkedIn included her among the 10 Top Voices in Software Development in 2019, and Top Voices in Data Science & AI in 2020.