
Sách keo gáy, Bìa mềm
Thể loại:Computers - Computer Science
Năm:2019
Ngôn ngữ:english
Trang:219
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 Spark’s 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.
What You'll Learn
Develop pipelines for streaming data processing using PySpark
Build Machine Learning & Deep Learning models using PySpark latest offerings
Use graph analytics using PySpark
Create Sequence Embeddings from Text data
Who This Book is For
Data
Scientists, machine learning and deep learning engineers who want to
learn and use PySpark for real time analysis on streaming data.
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