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| Main Authors: | , , , , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
[Erscheinungsort nicht ermittelbar]
O'REILLY MEDIA
2022
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| Subjects: | |
| Links: | https://learning.oreilly.com/library/view/-/9781098103644/?ar |
| Summary: | 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. |
| Physical Description: | 1 online resource |
| ISBN: | 9781098103620 1098103629 |
Staff View
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| spelling | Tandon, Akash VerfasserIn aut ADVANCED ANALYTICS WITH PYSPARK patterns for learning from data at scale using Python and Spark Akash Tandon, Sandy Ryza, Uri Laserson, Sean Owen & Josh Wills [Erscheinungsort nicht ermittelbar] O'REILLY MEDIA 2022 1 online resource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. SPARK (Electronic resource) Python (Computer program language) Data mining Python (Langage de programmation) Exploration de données (Informatique) Owen, Sean VerfasserIn aut Wills, Josh VerfasserIn aut Ryza, Sandy VerfasserIn aut Laserson, Uri 1983- VerfasserIn aut 1098103653 Erscheint auch als Druck-Ausgabe 1098103653 |
| spellingShingle | Tandon, Akash Owen, Sean Wills, Josh Ryza, Sandy Laserson, Uri 1983- ADVANCED ANALYTICS WITH PYSPARK patterns for learning from data at scale using Python and Spark SPARK (Electronic resource) Python (Computer program language) Data mining Python (Langage de programmation) Exploration de données (Informatique) |
| title | ADVANCED ANALYTICS WITH PYSPARK patterns for learning from data at scale using Python and Spark |
| title_auth | ADVANCED ANALYTICS WITH PYSPARK patterns for learning from data at scale using Python and Spark |
| title_exact_search | ADVANCED ANALYTICS WITH PYSPARK patterns for learning from data at scale using Python and Spark |
| title_full | ADVANCED ANALYTICS WITH PYSPARK patterns for learning from data at scale using Python and Spark Akash Tandon, Sandy Ryza, Uri Laserson, Sean Owen & Josh Wills |
| title_fullStr | ADVANCED ANALYTICS WITH PYSPARK patterns for learning from data at scale using Python and Spark Akash Tandon, Sandy Ryza, Uri Laserson, Sean Owen & Josh Wills |
| title_full_unstemmed | ADVANCED ANALYTICS WITH PYSPARK patterns for learning from data at scale using Python and Spark Akash Tandon, Sandy Ryza, Uri Laserson, Sean Owen & Josh Wills |
| title_short | ADVANCED ANALYTICS WITH PYSPARK |
| title_sort | advanced analytics with pyspark patterns for learning from data at scale using python and spark |
| title_sub | patterns for learning from data at scale using Python and Spark |
| topic | SPARK (Electronic resource) Python (Computer program language) Data mining Python (Langage de programmation) Exploration de données (Informatique) |
| topic_facet | SPARK (Electronic resource) Python (Computer program language) Data mining Python (Langage de programmation) Exploration de données (Informatique) |
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