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The Resource Practical data analysis : transform, model, and visualize your data through hands-on projects, developed in open source tools, Hector Cuesta

Practical data analysis : transform, model, and visualize your data through hands-on projects, developed in open source tools, Hector Cuesta

Label
Practical data analysis : transform, model, and visualize your data through hands-on projects, developed in open source tools
Title
Practical data analysis
Title remainder
transform, model, and visualize your data through hands-on projects, developed in open source tools
Statement of responsibility
Hector Cuesta
Creator
Subject
Language
eng
Summary
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 --
Member of
Assigning source
Provided by Publisher
Cataloging source
LWU
http://library.link/vocab/creatorName
Cuesta, Hector
Index
no index present
Literary form
non fiction
Series statement
Community experience distilled
http://library.link/vocab/subjectName
  • Data mining
  • Electronic data processing
  • Information visualization
  • Big data
  • Information retrieval
Label
Practical data analysis : transform, model, and visualize your data through hands-on projects, developed in open source tools, Hector Cuesta
Instantiates
Publication
Note
Includes index
Carrier category
volume
Carrier category code
  • nc
Carrier MARC source
rdacarrier.
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent.
Contents
Preface Chapter 1: Getting Started Chapter 2: Working with Data Chapter 3: Data Visualization Chapter 4: Text Classification Chapter 5: Similarity-based Image Retrieval Chapter 6: Simulation of Stock Prices Chapter 7: Predicting Gold Prices Chapter 8: Working with Support Vector Machines Chapter 9: Modeling Infectious Disease with Cellular Automata Chapter 10: Working with Social Graphs Chapter 11: Sentiment Analysis of Twitter Data Chapter 12: Data Processing and Aggregation with MongoDB Chapter 13: Working with MapReduce Chapter 14: Online Data Analysis with IPython and Wakari Appendix: Setting Up the Infrastructure Index
Control code
FIEb1746772x
Dimensions
24 cm.
Extent
vii, 335 pages
Isbn
9781783280995
Media category
unmediated
Media MARC source
rdamedia.
Media type code
  • n
Other physical details
illustrations
System control number
(OCoLC)868747975
Label
Practical data analysis : transform, model, and visualize your data through hands-on projects, developed in open source tools, Hector Cuesta
Publication
Note
Includes index
Carrier category
volume
Carrier category code
  • nc
Carrier MARC source
rdacarrier.
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent.
Contents
Preface Chapter 1: Getting Started Chapter 2: Working with Data Chapter 3: Data Visualization Chapter 4: Text Classification Chapter 5: Similarity-based Image Retrieval Chapter 6: Simulation of Stock Prices Chapter 7: Predicting Gold Prices Chapter 8: Working with Support Vector Machines Chapter 9: Modeling Infectious Disease with Cellular Automata Chapter 10: Working with Social Graphs Chapter 11: Sentiment Analysis of Twitter Data Chapter 12: Data Processing and Aggregation with MongoDB Chapter 13: Working with MapReduce Chapter 14: Online Data Analysis with IPython and Wakari Appendix: Setting Up the Infrastructure Index
Control code
FIEb1746772x
Dimensions
24 cm.
Extent
vii, 335 pages
Isbn
9781783280995
Media category
unmediated
Media MARC source
rdamedia.
Media type code
  • n
Other physical details
illustrations
System control number
(OCoLC)868747975

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