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

Machine learning with Pyspark with natural language processing and recommender systems

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...

Descripción completa

Detalles Bibliográficos
Otros Autores: Singh, Pramod, 1954- author (author)
Formato: Libro electrónico
Idioma:Inglés
Publicado: New York, NY : Apress [2022]
Edición:Second edition
Materias:
Application software > Development.
Python (Computer program language)
SPARK (Computer program language)
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009644291506719
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.

Ejemplares similares