Practical Data Analysis

More Information
Learn
  • Work with data to get meaningful results from your data analysis projects
  • Visualize your data to find trends and correlations
  • Build your own image similarity search engine
  • Learn how to forecast numerical values from time series data
  • Create an interactive visualization for your social media graph
  • Explore the MapReduce framework in MongoDB
  • Create interactive simulations with D3js
About

Plenty of small businesses face big amounts of data but lack the internal skills to support quantitative analysis. Understanding how to harness the power of data analysis using the latest open source technology can lead them to providing better customer service, the visualization of customer needs, or even the ability to obtain fresh insights about the performance of previous products. Practical Data Analysis is a book ideal for home and small business users who want to slice and dice the data they have on hand with minimum hassle.

Practical Data Analysis is a hands-on guide to understanding the nature of your data and turn it into insight. It will introduce you to the use of machine learning techniques, social networks analytics, and econometrics to help your clients get insights about the pool of data they have at hand. Performing data preparation and processing over several kinds of data such as text, images, graphs, documents, and time series will also be covered.

Practical Data Analysis presents a detailed exploration of the current work in data analysis through self-contained projects. First you will explore the basics of data preparation and transformation through OpenRefine. Then you will get started with exploratory data analysis using the D3js visualization framework. You will also be introduced to some of the machine learning techniques such as, classification, regression, and clusterization through practical projects such as spam classification, predicting gold prices, and finding clusters in your Facebook friends’ network. You will learn how to solve problems in text classification, simulation, time series forecast, social media, and MapReduce through detailed projects. Finally you will work with large amounts of Twitter data using MapReduce to perform a sentiment analysis implemented in Python and MongoDB.

Practical Data Analysis contains a combination of carefully selected algorithms and data scrubbing that enables you to turn your data into insight.

Features
  • Explore how to analyze your data in various innovative ways and turn them into insight
  • Learn to use the D3.js visualization tool for exploratory data analysis
  • Understand how to work with graphs and social data analysis
  • Discover how to perform advanced query techniques and run MapReduce on MongoDB
Page Count 360
Course Length 10 hours 48 minutes
ISBN 9781783280995
Date Of Publication 21 Oct 2013

Authors

Hector Cuesta

Hector Cuesta is founder and Chief Data Scientist at Dataxios, a machine intelligence research company. Holds a BA in Informatics and a M.Sc. in Computer Science. He provides consulting services for data-driven product design with experience in a variety of industries including financial services, retail, fintech, e-learning and Human Resources. He is an enthusiast of Robotics in his spare time.

You can follow him on Twitter at https://twitter.com/hmCuesta.