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Published by Packt Publishing, Birmingham, 2016
ISBN 10: 1785289713 ISBN 13: 9781785289712
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condition: new. Paperback. A practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache Spark About This Book * Learn to use various data analysis tools and algorithms to classify, cluster, visualize, simulate, and forecast your data * Apply Machine Learning algorithms to different kinds of data such as social networks, time series, and images * A hands-on guide to understanding the nature of data and how to turn it into insight Who This Book Is For This book is for developers who want to implement data analysis and data-driven algorithms in a practical way. It is also suitable for those without a background in data analysis or data processing. Basic knowledge of Python programming, statistics, and linear algebra is assumed. What You Will Learn * Acquire, format, and visualize your data * Build an image-similarity search engine * Generate meaningful visualizations anyone can understand * Get started with analyzing social network graphs * Find out how to implement sentiment text analysis * Install data analysis tools such as Pandas, MongoDB, and Apache Spark * Get to grips with Apache Spark * Implement machine learning algorithms such as classification or forecasting In Detail Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you'll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark. Style and approach This is a hands-on guide to data analysis and data processing. The concrete examples are explained with simple code and accessible data. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Language: English
Published by Packt Publishing, Limited, 2013
ISBN 10: 1783280999 ISBN 13: 9781783280995
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. pp. 360 Index.
Language: English
Published by Packt Publishing, Limited, 2013
ISBN 10: 1783280999 ISBN 13: 9781783280995
Seller: Majestic Books, Hounslow, United Kingdom
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Published by Packt Publishing 2016-09-30, 2016
ISBN 10: 1785289713 ISBN 13: 9781785289712
Seller: Chiron Media, Wallingford, United Kingdom
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Published by Packt Publishing 2013-10-22, 2013
ISBN 10: 1783280999 ISBN 13: 9781783280995
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Language: English
Published by Packt Publishing, Birmingham, 2016
ISBN 10: 1785289713 ISBN 13: 9781785289712
Seller: AussieBookSeller, Truganina, VIC, Australia
Paperback. Condition: new. Paperback. A practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache Spark About This Book * Learn to use various data analysis tools and algorithms to classify, cluster, visualize, simulate, and forecast your data * Apply Machine Learning algorithms to different kinds of data such as social networks, time series, and images * A hands-on guide to understanding the nature of data and how to turn it into insight Who This Book Is For This book is for developers who want to implement data analysis and data-driven algorithms in a practical way. It is also suitable for those without a background in data analysis or data processing. Basic knowledge of Python programming, statistics, and linear algebra is assumed. What You Will Learn * Acquire, format, and visualize your data * Build an image-similarity search engine * Generate meaningful visualizations anyone can understand * Get started with analyzing social network graphs * Find out how to implement sentiment text analysis * Install data analysis tools such as Pandas, MongoDB, and Apache Spark * Get to grips with Apache Spark * Implement machine learning algorithms such as classification or forecasting In Detail Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you'll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark. Style and approach This is a hands-on guide to data analysis and data processing. The concrete examples are explained with simple code and accessible data. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Language: Chinese
Published by Machinery Industry Press, 2014
ISBN 10: 7111476239 ISBN 13: 9787111476238
Seller: liu xing, Nanjing, JS, China
paperback. Condition: New. Pub Date: 2014-09-01 Pages: 335 Language: Chinese Publisher: Machinery Industry Press Big Data Technology Series: Practical Data Analysis of 14 chapters: Chapter 1 discussed the basic principles of data analysis and data analysis step; 2 chapter explains how to clean and ready for data; Chapter 3 shows a visualization application D3.js in JavaScript visualization framework to implement various types of data; Chapter 4 describes how to use Bayesian algorithms to distinguish spam; 5 Application.
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Seller: PBShop.store US, Wood Dale, IL, U.S.A.
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Language: English
Published by Packt Publishing Limited, 2016
ISBN 10: 1785289713 ISBN 13: 9781785289712
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
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