Spark For Data Science Srinivas Duvvuri Bikramaditya Singhal by Srinivas Duvvuri, Bikramaditya Singhal 9781785885655, 1785885650 instant download after payment.

Analyze your data and delve deep into the world of machine learning with the latest Spark version, 2.0

• 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

This book is for anyone who wants to leverage Apache Spark for data science and machine learning. If you are a technologist who wants to expand your knowledge to perform data science operations in Spark, or a data scientist who wants to understand how algorithms are implemented in Spark, or a newbie with minimal development experience who wants to learn about Big Data Analytics, this book is for you!

• 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 RDD, DataFrame and Dataset APIs
• Become an expert by improving your data analytical skills

This is the era of Big Data. The words 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