Machine Learning with Spark – Tackle Big Data with Powerful Spark Machine Learning Algorithms
By 作者: Nick Pentreath
ISBN-10 书号: 1783288515
ISBN-13 书号: 9781783288519
Release Finelybook 出版日期: December 8, 2014
pages 页数: 329

$34.99

Create scalable machine learning applications to power a modern data-driven business using Spark
About This Book
A practical tutorial with real-world use cases allowing you to develop your own machine learning systems with Spark
Combine various techniques and models into an intelligent machine learning system
Use Spark’s powerful tools to load, analyze, clean, and transform your data
Who This Book Is For
If you are a Scala, Java, or Python developer with an interest in machine learning and data analysis and are eager to learn how to apply common machine learning techniques at scale using the Spark framework, this is the book for you. While it may be useful to have a basic understanding of Spark, no previous experience is required.
In Detail
Apache Spark is a framework for distributed computing that is designed from the ground up to be optimized for low latency tasks and in-memory data storage. It is one of the few frameworks for parallel computing that combines speed, scalability, in-memory processing, and fault tolerance with ease of programming and a flexible, expressive, and powerful API design.
This book guides you through the basics of Spark’s API used to load and process data and prepare the data to use as input to the various machine learning models. There are detailed examples and real-world use cases for you to explore common machine learning models including recommender systems, classification, regression, clustering, and dimensionality reduction. You will cover advanced topics such as working with large-scale text data, and methods for online machine learning and model evaluation using Spark Streaming.
Contents
Chapter 1. Getting Up and Running with Spark
Chapter 2. Designing a Machine Learning System
Chapter 3. Obtaining, Processing, and Preparing Data with Spark
Chapter 4. Building a Recommendation Engine with Spark
Chapter 5. Building a Classification Model with Spark
Chapter 6. Building a Regression Model with Spark
Chapter 7. Building a Clustering Model with Spark
Chapter 8. Dimensionality Reduction with Spark
Chapter 9. Advanced Text Processing with Spark
Chapter 10. Real-time Machine Learning with Spark Streaming
创建可扩展的机器学习应用程序,为使用Spark的现代数据驱动业务提供动力
关于这本书
具有真实用例的实用教程允许您使用Spark开发自己的机器学习系统
将各种技术和模型结合到智能机器学习系统中
使用Spark的强大工具来加载,分析,清理和转换数据
这本书是谁
如果您是Scala,Java或Python开发人员,对机器学习和数据分析感兴趣,并渴望学习如何使用Spark框架大规模应用常用的机器学习技术,这是为您提供的书。虽然对Spark有一个基本的了解可能是有用的,但不需要以前的经验。
详细
Apache Spark是分布式计算的框架,从底层设计,可针对低延迟任务和内存中数据存储进行优化。它是并行计算的几个框架之一,它结合了速度,可扩展性,内存中处理和容错以及易于编程和灵活,富有表现力和强大的API设计。
本书引导您了解用于加载和处理数据的Spark API的基础知识,并准备数据以用作各种机器学习模型的输入。有一些详细的例子和真实的用例来探索常见的机器学习模型,包括推荐系统,分类,回归,聚类和降维。您将涵盖高级主题,如使用大型文本数据,以及使用Spark Streaming进行在线计算机学习和模型评估的方法。
目录
第一章使用Spark开始运行
第二章设计机器学习系统
第3章使用Spark获取,处理和准备数据
第4章使用Spark构建推荐引擎
第5章使用Spark构建分类模型
第六章用Spark构建回归模型
第7章使用Spark构建集群模型
第八章用火花减少尺寸
第9章使用Spark进行高级文本处理
第10章使用Spark Streaming实时机器学习
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Machine Learning with Spark – Tackle Big Data with Powerful Spark Machine Learning Algorithms

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