74.298 resultater (1,09094 sekunder)

Vis alle filtre

Mærke

Vis alle

Farve

Vis alle

Størrelse

Vis alle

Køn

Butik

Vis alle

Pris (EUR)

Nulstil filter

Produkter
Fra
Butikker

The Political Machine - Assembling Sovereignty in the Bronze Age Caucasus - Adam T. Smith

The Political Machine - Assembling Sovereignty in the Bronze Age Caucasus - Adam T. Smith

\This provocative and timely book identifies three main phases in the development of 'sovereign assemblage' and provides a compelling account of social change in Caucasian societies between the fourth millennium and the Iron Age. Peppered with erudite case studies, this original and important book will be widely read and used by archaeologists, anthropologists, and art historians.\--David Wengrow, University College London\In The Political Machine, Smith presents a cogent and sophisticated paradigm..

DKK 283.95
2

Machine Learning Systems - Jeff Smith - Bog - Manning Publications - Plusbog.dk

Machine Learning Systems - Jeff Smith - Bog - Manning Publications - Plusbog.dk

Summary Machine Learning Systems: Designs that scale is an example-rich guide that teaches you how to implement reactive design solutions in your machine learning systems to make them as reliable as a well-built web app. Foreword by Sean Owen, Director of Data Science, Cloudera Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology If you’re building machine learning models to be used on a small scale, you don't need this book. But if you're a developer building a production-grade ML application that needs quick response times, reliability, and good user experience, this is the book for you. It collects principles and practices of machine learning systems that are dramatically easier to run and maintain, and that are reliably better for users. About the Book Machine Learning Systems: Designs that scale teaches you to design and implement production-ready ML systems. You'll learn the principles of reactive design as you build pipelines with Spark, create highly scalable services with Akka, and use powerful machine learning libraries like MLib on massive datasets. The examples use the Scala language, but the same ideas and tools work in Java, as well. What's Inside - - Working with Spark, MLlib, and Akka - - Reactive design patterns - - Monitoring and maintaining a large-scale system - - Futures, actors, and supervision - About the Reader Readers need intermediate skills in Java or Scala. No prior machine learning experience is assumed. About the Author Jeff Smith builds powerful machine learning systems. For the past decade, he has been working on building data science applications, teams, and companies as part of various teams in New York, San Francisco, and Hong Kong. He blogs (https: //medium.com/@jeffksmithjr), tweets (@jeffksmithjr), and speaks (www.jeffsmith.tech/speaking) about various aspects of building real-world machine learning systems. Table of Contents PART 1 - FUNDAMENTALS OF REACTIVE MACHINE LEARNING 1) 1) Learning reactive machine learning 1) 1) Using reactive tools 1) PART 2 - BUILDING A REACTIVE MACHINE LEARNING SYSTEM 1) 1) Collecting data 1) 1) Generating features 1) 1) Learning models 1) 1) Evaluating models 1) 1) Publishing models 1) 1) Responding 1) PART 3 - OPERATING A MACHINE LEARNING SYSTEM 1) 1) Delivering 1) 1) Evolving intelligence 1)

DKK 370.00
1