Unlock the complexities of machine learning algorithms in Spark to generate useful data insights through this data analysis tutorial

About This Book

Process and analyze big data in a distributed and scalable way

Write sophisticated Spark pipelines that incorporate elaborate extraction

Build and use regression models to predict flight delays

Who This Book Is For

Are you a developer with a background in machine learning and statistics who is feeling limited by the current slow and “small data” machine learning tools? Then this is the book for you! In this book, you will create scalable machine learning applications to power a modern data-driven business using Spark. We assume that you already know the machine learning concepts and algorithms and have Spark up and running (whether on a cluster or locally) and have a basic knowledge of the various libraries contained in Spark.

What You Will Learn

Use Spark streams to cluster tweets online

Run the PageRank algorithm to compute user influence

Perform complex manipulation of DataFrames using Spark

Define Spark pipelines to compose individual data transformations

Utilize generated models for off-line/on-line prediction

Transfer the learning from an ensemble to a simpler Neural Network

Understand basic graph properties and important graph operations

Use GraphFrames, an extension of DataFrames to graphs, to study graphs using an elegant query language

Use K-means algorithm to cluster movie reviews dataset

In Detail

The purpose of machine

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