English | ISBN: 1785885650 | 2016 | PDF | 339 Pages | 13 MB

Key Features
Perform data analysis and build predictive models on huge datasets that leverage Apache Spark
Learn to integrate data science algorithms and techniques with the fast and scalable computing features of Spark to address big data challenges
Work through practical examples on real-world problems with sample code snippets
Book Description
This is the era of Big Data and Internet of Things! Big Data implies big innovation and enables a competitive advantage for businesses. Apache Spark was designed to perform Big Data analytics at scale, and so Spark is equipped with the necessary algorithms and supports multiple programming languages.

Whether you are a technologist, a data scientist, or a beginner to Big Data analytics, this book will provide you with all the skills necessary to perform statistical data analysis, data visualization, predictive modeling, and build scalable data products or solutions using Python, Scala, and R.

With ample case studies and real-world examples, Spark for Data Science will help you ensure the successful execution of your data science projects.

What you will learn
Consolidate, clean, and transform your data acquired from various data sources
Perform statistical analysis of data to find hidden insights
Explore graphical techniques to see what your data looks like
Use machine learning techniques to build predictive models
Build scalable data products and solutions
Start programming using the RADD API
Become an expert by improving your data analytical skills