September 2016
Beginner to intermediate
344 pages
7h 44m
English
Overview
Explore how to leverage Apache Spark for efficient big data analytics and machine learning solutions in "Spark for Data Science". This detailed guide provides you with the skills to process massive datasets, perform data analytics, and build predictive models using Spark's powerful tools like RDDs, DataFrames, and Datasets.
What this Book will help me do
- Gain expertise in data processing and transformation with Spark.
- Perform advanced statistical analysis to uncover insights.
- Master machine learning techniques to create predictive models using Spark.
- Utilize Spark's APIs to process and visualize big data.
- Build scalable and efficient data science solutions.
Author(s)
This book is co-authored by None Singhal and None Duvvuri, both accomplished data scientists with extensive experience in Apache Spark and big data technologies. They bring their practical industry expertise to explain complex topics in a straightforward manner. Their writing emphasizes real-world applications and step-by-step procedural guidance, making this a valuable resource for learners.
Who is it for?
This book is ideally suited for technologists seeking to incorporate data science capabilities into their work with Apache Spark, data scientists interested in machine learning algorithms implemented in Spark, and beginners aiming to step into the field of big data analytics. Whether you are familiar with Spark or completely new, this book offers valuable insights and practical knowledge.
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