Practical Data Analysis - Transform, model, and visualize your data through hands-on projects, developed in open source tools

Practical Data Analysis - Transform, model, and visualize your data through hands-on projects, developed in open source tools

A hands-on guide to understanding the nature of your data and turn it into insight. Presents a detailed exploration of the current work in data analysis through self-contained projects.

Publication date: 22 Oct 2013

ISBN-10: 1783280999

ISBN-13: 978-178328099

Paperback: 360 pages

Views: 1,118

Type: Book

Publisher: Packt Publishing

License: n/a

Post time: 03 May 2017 09:30:00

Practical Data Analysis - Transform, model, and visualize your data through hands-on projects, developed in open source tools

Practical Data Analysis - Transform, model, and visualize your data through hands-on projects, developed in open source tools A hands-on guide to understanding the nature of your data and turn it into insight. Presents a detailed exploration of the current work in data analysis through self-contained projects.
Tag(s): Big Data Data Science Machine Learning
Publication date: 22 Oct 2013
ISBN-10: 1783280999
ISBN-13: 978-178328099
Paperback: 360 pages
Views: 1,118
Document Type: Book
Publisher: Packt Publishing
License: n/a
Post time: 03 May 2017 09:30:00
From the Book Description:
Hector Cuesta wrote: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.




About The Author(s)


Hector Cuesta holds a B.A in Informatics and M.Sc. in Computer Science. He provides consulting services for software engineering and data analysis with experience in a variety of industries including financial services, social networking, e-learning, and human resources. He is a lecturer in the Department of Computer Science at the Autonomous University of Mexico State (UAEM). His main research interests lie in computational epidemiology, machine learning, computer vision, high-performance computing, big data, simulation, and data visualization.

Hector Cuesta

Hector Cuesta holds a B.A in Informatics and M.Sc. in Computer Science. He provides consulting services for software engineering and data analysis with experience in a variety of industries including financial services, social networking, e-learning, and human resources. He is a lecturer in the Department of Computer Science at the Autonomous University of Mexico State (UAEM). His main research interests lie in computational epidemiology, machine learning, computer vision, high-performance computing, big data, simulation, and data visualization.


Book Categories