Learn PySpark : build Python-based machine learning and deep learning models / Pramod Singh.
Singh, Pramod, author.
2019
QA76.73.S59 S56 2019eb
Available Online

Linked e-resources

Linked Resource Online Access
Concurrent users Unlimited
Authorized users Authorized users
Document Delivery Supplied Can lend chapters, not whole ebooks

Details

Title Learn PySpark : build Python-based machine learning and deep learning models / Pramod Singh.
Author Singh, Pramod, author.
ISBN 9781484249611 (electronic book)
1484249615 (electronic book)
9781484249604
DOI https://doi.org/10.1007/978-1-4842-4961-1
https://doi.org/10.1007/978-1-4842-4
Published New York : Apress, [2019]
Copyright ©2019
Language English
Description 1 online resource : illustrations
Item Number 10.1007/978-1-4842-4961-1 doi
10.1007/978-1-4842-4
Call Number QA76.73.S59 S56 2019eb
Dewey Decimal Classification 006.3/1
Summary Leverage machine and deep learning models to build applications on real-time data using PySpark. This book is perfect for those who want to learn to use this language to perform exploratory data analysis and solve an array of business challenges. You'll start by reviewing PySpark fundamentals, such as Sparks core architecture, and see how to use PySpark for big data processing like data ingestion, cleaning, and transformations techniques. This is followed by building workflows for analyzing streaming data using PySpark and a comparison of various streaming platforms. You'll then see how to schedule different spark jobs using Airflow with PySpark and book examine tuning machine and deep learning models for real-time predictions. This book concludes with a discussion on graph frames and performing network analysis using graph algorithms in PySpark. All the code presented in the book will be available in Python scripts on Github.
Note Includes index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed September 23, 2019).
Available in Other Form Learn Pyspark : Build Python-Based Machine Learning and Deep Learning Models
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
Chapter 1: Introduction to PySpark
Chapter 2: Data Processing
Chapter 3: Spark Structured Streaming
Chapter 4: Airflow
Chapter 5: Machine Learning Library (MLlib)
Chapter 6: Supervised Machine Learning
Chapter 7: Unsupervised Machine Learning
Chapter 8: Deep Learning Using PySpark.

Browse Subjects

Show more subjects...

Statistics

from
to
Export