Advanced Analytics with PySpark: Patterns for Learning from Data at Scale Using Python and Spark
Publication details: Mumbai: Shroff Publishers & Distributors Pvt. Ltd., 2022Description: 220ISBN:- 9789355422804
- 006.312 TAN
Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
---|---|---|---|---|---|---|---|---|
Book | Alliance College of Engineering and Design | CSE & IT | 006.312 TAN (Browse shelf(Opens below)) | Available | E12341 |
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006.312 SIN Data warehousing | 006.312 SOU Visual data mining | 006.312 TAN Data mining with SQL Server 2005 | 006.312 TAN Advanced Analytics with PySpark: Patterns for Learning from Data at Scale Using Python and Spark | 006.312 THA Data Science and Machine Learning With R | 006.312 VAN Python Data Science Handbook: Essential Tools for Working with Data | 006.312 VAN Python Data Science Handbook: Essential Tools for Working with Data |
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.
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