Akash Tandon, Sandy Ryza, Uri Laserson, Sean Owen, Josh Wills

Advanced Analytics with PySpark (eBook, ePUB)

• Format: ePub

Produktbeschreibung

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 ecosystemLearn general approaches in data scienceExamine complete implementations that analyze large public datasetsDiscover which machine learning tools make sense for particular problemsExplore code that can be adapted to many uses

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Produktdetails

• Verlag: O'Reilly Media
• Seitenzahl: 236
• Erscheinungstermin: 14. Juni 2022
• Englisch
• ISBN-13: 9781098103606
• Artikelnr.: 72362384

Autorenporträt

Akash Tandon is an independent consultant and experienced full-stack data engineer. Previously, he was a senior data engineer at Atlan, where he built software for enterprise data science teams. In another life, he had worked on data science projects for governments, and built risk assessment tools at a FinTech startup. As a student, he wrote open source software with the R project for statistical computing and Google. In his free time, he researches things for no good reason.