Machine learning with Pyspark : with natural language processing and recommender systems /

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Master the new features in PySpark 3.1 to develop data-driven, intelligent applications. This updated edition covers topics ranging from building scalable machine learning models, to natural language processing, to recommender systems. Machine Learning with PySpark, Second Edition begins with the fu...

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Bibliographic Details
Call Number:Libro Electrónico
Main Author: Singh, Pramod (Author)
Format: Electronic eBook
Language:Inglés
Published: California: Apress, [2022]
Edition:Second edition.
Subjects:
Application software > Development.
Python (Computer program language)
SPARK (Computer program language)
Logiciels d'application > Développement.
Python (Langage de programmation)
Online Access:Texto completo
Table of Contents:
  • Chapter 1: Introduction to Spark 3.1
  • Chapter 2: Manage Data with PySpark
  • Chapter 3: Introduction to Machine Learning
  • Chapter 4: Linear Regression with PySpark
  • Chapter 5: Logistic Regression with PySpark
  • Chapter 6: Ensembling with PySpark
  • Chapter 7: Clustering with PySpark
  • Chapter 8: Recommendation Engine with PySpark
  • Chapter 9: Advanced Feature Engineering with PySpark.

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