Scaling Machine Learning with Spark: Distributed ML with MLlib, TensorFlow, and PyTorch - Brossura

Polak, Adi

 
9781098106829: Scaling Machine Learning with Spark: Distributed ML with MLlib, TensorFlow, and PyTorch
Brossura
ISBN 10: 1098106822 ISBN 13: 9781098106829
Casa editrice: O'Reilly Media, 2023

Sinossi

Learn how to build end-to-end scalable machine learning solutions with Apache Spark. With this practical guide, author Adi Polak introduces data and ML practitioners to creative solutions that supersede today's traditional methods. You'll learn a more holistic approach that takes you beyond specific requirements and organizational goals--allowing data and ML practitioners to collaborate and understand each other better.

Scaling Machine Learning with Spark examines several technologies for building end-to-end distributed ML workflows based on the Apache Spark ecosystem with Spark MLlib, MLflow, TensorFlow, and PyTorch. If you're a data scientist who works with machine learning, this book shows you when and why to use each technology.

You will:

  • Explore machine learning, including distributed computing concepts and terminology
  • Manage the ML lifecycle with MLflow
  • Ingest data and perform basic preprocessing with Spark
  • Explore feature engineering, and use Spark to extract features
  • Train a model with MLlib and build a pipeline to reproduce it
  • Build a data system to combine the power of Spark with deep learning
  • Get a step-by-step example of working with distributed TensorFlow
  • Use PyTorch to scale machine learning and its internal architecture

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Editore
O'Reilly Media
Data di pubblicazione
2023
Lingua
Inglese
ISBN 10 
1098106822
ISBN 13 
9781098106829
Rilegatura
Copertina flessibile
Numero di pagine
291
Contatto del produttore
non disponibile
Persona responsabile
non disponibile