Mastering Machine Learning with Spark
內容描述
Key FeaturesProcess and analyze big data in a distributed and scalable wayWrite sophisticated Spark pipelines that incorporate elaborate extractionBuild and use regression models to predict flight delaysBook DescriptionThe purpose of machine learning is to build systems that learn from data. Being able to understand trends and patterns in complex data is critical to success; it is one of the key strategies to unlock growth in the challenging contemporary marketplace today. With the meteoric rise of machine learning, developers are now keen on finding out how can they make their Spark applications smarter.This book gives you access to transform data into actionable knowledge. The book commences by defining machine learning primitives by the MLlib and H2O libraries. You will learn how to use Binary classification to detect the Higgs Boson particle in the huge amount of data produced by CERN particle collider and classify daily health activities using ensemble Methods for Multi-Class Classification.Next, you will solve a typical regression problem involving flight delay predictions and write sophisticated Spark pipelines. You will analyze Twitter data with help of the doc2vec algorithm and K-means clustering. Finally, you will build different pattern mining models using MLlib, perform complex manipulation of DataFrames using Spark and Spark SQL, and deploy your app in a Spark streaming environment.What you will learnUse Spark streams to cluster tweets onlineRun the PageRank algorithm to compute user influencePerform complex manipulation of DataFrames using SparkDefine Spark pipelines to compose individual data transformationsUtilize generated models for off-line/on-line predictionTransfer the learning from an ensemble to a simpler Neural Network
