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Advanced Analytics with Spark: Patterns for Learning from Data at Scale

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In this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example.

You’ll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniques—classification, collaborative filtering, and anomaly detection among others—to fields such as genomics, security, and finance. If you have an entry-level understanding of machine learning and statistics, and you program in Java, Python, or Scala, you’ll find these patterns useful for working on your own data applications.

Patterns include:

  • Recommending music and the Audioscrobbler data set
  • Predicting forest cover with decision trees
  • Anomaly detection in network traffic with K-means clustering
  • Understanding Wikipedia with Latent Semantic Analysis
  • Analyzing co-occurrence networks with GraphX
  • Geospatial and temporal data analysis on the New York City Taxi Trips data
  • Estimating financial risk through Monte Carlo simulation
  • Analyzing genomics data and the BDG project
  • Analyzing neuroimaging data with PySpark and Thunder
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The Martian Principles for Successful Enterprise Systems: 20 Lessons Learned from NASAs Mars Exploration Rover Mission
The Martian Principles for Successful Enterprise Systems: 20 Lessons Learned from NASAs Mars Exploration Rover Mission
When you need to land and operate a robot on Mars, "halfway" software is not an option. While helping to develop the Collaborative Information Portal, or CIP, for NASA's Mars Exploration Rover mission, Ronald Mak identified and refined a set of principles that represent the fundamental goals necessary for any successful enterprise system....
Handbook of Time Series Analysis, Signal Processing, and Dynamics
Handbook of Time Series Analysis, Signal Processing, and Dynamics

It is hoped that this book will serve both as a text in time-series analysis and signal processing and as a reference book for research workers and practitioners. Timeseries analysis and signal processing are two subjects which ought to be treated as one; and they are the concern of a wide range of applied disciplines including statistics,...

Scala for Machine Learning
Scala for Machine Learning

Leverage Scala and Machine Learning to construct and study systems that can learn from data

About This Book

  • Explore a broad variety of data processing, machine learning, and genetic algorithms through diagrams, mathematical formulation, and source code
  • Leverage your expertise in Scala...

Professional Java for Web Applications
Professional Java for Web Applications

The comprehensive Wrox guide for creating Java web applications for the enterprise

This guide shows Java software developers and software engineers how to build complex web applications in an enterprise environment. You'll begin with an introduction to the Java Enterprise Edition and the basic web application, then set...

Design of Logic-based Intelligent Systems
Design of Logic-based Intelligent Systems

Principles for constructing intelligent systems
Design of Logic-based Intelligent Systems develops principles andmethods for constructing intelligent systems for complex tasks thatare readily done by humans but are difficult for machines. CurrentArtificial Intelligence (AI) approaches rely on various constructsand methods (production
...

Advanced Programming in the UNIX Environment, 3rd Edition
Advanced Programming in the UNIX Environment, 3rd Edition

For more than twenty years, serious C programmers have relied on one book for practical, in-depth knowledge of the programming interfaces that drive the UNIX and Linux kernels: W. Richard Stevens’ Advanced Programming in the UNIX® Environment . Now, once again, Rich’s colleague Steve...

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