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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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Singh, Pramod (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: California: Apress, [2022]
Edición:Second edition.
Temas:
Application software > Development.
Python (Computer program language)
SPARK (Computer program language)
Logiciels d'application > Développement.
Python (Langage de programmation)
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 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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