Use PySpark to easily crush messy data at-scale and discover proven techniques to create testable, immutable, and easily parallelizable Spark jobsKey FeaturesWork with large amounts of agile data using distributed datasets and in-memory cachingSource data from all popular data hosting platforms, such as HDFS, Hive, JSON, and S3Employ the easy-to-use PySpark API to deploy big data Analytics for productionBook DescriptionApache Spark is an open source parallel-processing framework that has been around for quite some time now.
This Handbook documents the main trends in current research between logic and language, including its broader influence in computer science, linguistic theory and cognitive science.
A practical guide to programming for data acquisition and measurement - must-have info in just the right amount of depth for engineers who are not programming specialists.
The 21 chapters in this handbook are written by the leading experts in the world on the theory, techniques, applications, and standards surrounding lossless compression.
Given modern society's need to control its ever-increasing body of information, digital libraries will be among the most important and influential institutions of this century.
This volume is a self-contained, exhaustive exposition of the extrapolation methods theory, and of the various algorithms and procedures for accelerating the convergence of scalar and vector sequences.
Data Analysis Methods in Physical Oceanography is a practical referenceguide to established and modern data analysis techniques in earth and oceansciences.
Explore the world of neural networks by building powerful deep learning models using the R ecosystemKey FeaturesGet to grips with the fundamentals of deep learning and neural networksUse R 3.
The ambition of this volume is twofold: to provide a comprehensive overview of the field and to serve as an indispensable reference work for anyone who wants to work in it.
