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During the early part of the 20th century farming in America was transformed from a pre-industrial to an industrial activity. This book explores the modernization of the 1920s, which saw farmers adopt not just new technology, but also the financial cultural & ideological apparatus of industrialism.
Ben introduces his personal toolbox of techniques for building deployable and maintainable production machine learning systems. You'll learn the importance of Agile methodologies for fast prototyping and conferring with stakeholders, while developing a new appreciation for the importance of planning. Adopting well-established software development standards will help you deliver better code management, and make it easier to test, scale, and even reuse your machine learning code. Every method is explained in a friendly, peer-to-peer style and illustrated with production-ready source code. About the Technology Deliver maximum performance from your models and data. This collection of reproducible techniques will help you build stable data pipelines, efficient application workflows, and maintainable models every time. Based on decades of good software engineering practice, machine learning engineering ensures your ML systems are resilient, adaptable, and perform in production. .
List for March 7, 1844, is the list for September 10, 1842, amended in manuscript.
Vols. for 1963- include as pt. 2 of the Jan. issue: Medical subject headings.