ISBN:
9781098103620
,
1098103629
Language:
English
Pages:
1 online resource (41 pages)
Edition:
1st edition
Parallel Title:
Erscheint auch als
DDC:
006.3/12
Keywords:
SPARK (Electronic resource)
;
Python (Computer program language)
;
Data mining
;
Electronic books ; local
;
Electronic books
;
Data mining
;
Python (Computer program language)
;
SPARK (Electronic resource)
Abstract:
The amount of data being generated today is staggering. And growing. Apache Spark has emerged as the de facto tool to analyze big data and is now a critical part of the data science toolbox. Updated for Spark 3.0, this practical guide brings together Spark, statistical methods, and real-world datasets to teach you how to approach analytics problems using PySpark, Spark's Python API, and other best practices in Spark programming. Data scientists Akash Tandon, Sandy Ryza, Uri Laserson, Sean Owen, and Josh Wills offer an introduction to the Spark ecosystem, then dive into patterns that apply common techniques--including classification, clustering, collaborative filtering, and anomaly detection--to fields such as genomics, security, and finance. This updated edition also covers NLP and image processing. If you have a basic understanding of machine learning and statistics and you program in Python, this book will get you started with large-scale data analysis. Familiarize yourself with Spark's programming model and ecosystem Learn general approaches in data science Examine complete implementations that analyze large public datasets Discover which machine learning tools make sense for particular problems Explore code that can be adapted to many uses
Note:
Online resource; Title from title page (viewed April 25, 2022)
,
Mode of access: World Wide Web.
