Название: Implementing MLOps in the Enterprise: A Production-First Approach
Автор: Yaron Haviv, Noah Gift
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 377
Язык: английский
Формат: epub (true)
Размер: 15.5 MB
With demand for scaling, real-time access, and other capabilities, businesses need to consider building operational machine learning pipelines. This practical guide helps your company bring data science to life for different real-world MLOps scenarios. Senior data scientists, MLOps engineers, and machine learning engineers will learn how to tackle challenges that prevent many businesses from moving ML models to production. Authors Yaron Haviv and Noah Gift take a production-first approach. Rather than beginning with the ML model, you'll learn how to design a continuous operational pipeline, while making sure that various components and practices can map into it. By automating as many components as possible, and making the process fast and repeatable, your pipeline can scale to match your organization's needs. You'll learn how to provide rapid business value while answering dynamic MLOps requirements. This book is for practitioners in charge of building, managing, maintaining, and operationalizing the Data Science process end to end: the heads of Data Science, heads of ML engineering, senior data scientists, MLOps engineers, and Machine Learning engineers. These practitioners are familiar with the nooks and crannies (as well as the challenges and obstacles) of the Data cience pipeline, and they have the initial technological know-how, for example, in Python, Pandas, Sklearn, and others.
Название: Принятие решений в условиях неопределенности
