Building custom transformers and estimators to extend PySpark's ML Pipelines.

ML Pipelines are one of the best way to organize your ML code. In this video, we extend PySpark's ML Pipelines with our own components. Flexible, powerful, fast, pick three!.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Formato: Electrónico Video
Idioma:Inglés
Publicado: [Place of publication not identified] : Manning Publications, 2021.
Edición:[First edition].
Temas:
Application software > Development.
Python (Computer program language)
SPARK (Computer program language)
Logiciels d'application > Développement.
Python (Langage de programmation)
Webcast
Instructional films.
Internet videos.
Nonfiction films.
Films de formation.
Films autres que de fiction.
Vidéos sur Internet.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Descripción
Sumario:ML Pipelines are one of the best way to organize your ML code. In this video, we extend PySpark's ML Pipelines with our own components. Flexible, powerful, fast, pick three!.
Descripción Física:1 online resource (1 video file (59 min.)) : sound, color.
Tiempo de Juego:00:59:00

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