Practical Data Analysis by Cuesta Hector (38 results)

Condition: good. A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships via media mail.…

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Paperback. Condition: Good. Plenty of small businesses face big amounts of data but lack the internal skills to support quantitative analysis. This book explains how to harness the power of data analysis using the latest open source technology so that companies may provide better customer service, visualize customer needs and even obtain fresh insights about the performance of previous products. …

Condition: Very Good. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

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paperback. Condition: New. 2nd Revised edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

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Condition: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,750grams, ISBN:9781783280995.

Digital. Condition: New. A practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache SparkAbout 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 insightWho This Book Is ForThis 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 forecastingIn DetailBeyond 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 approachThis is a hands-on guide to data analysis and data processing. The concrete examples are explained with simple code and accessible data.…

Condition: New. pp. 360 Index.

Condition: New. pp. 360 3:B&W 7.5 x 9.25 in or 235 x 191 mm Perfect Bound on White w/Gloss Lam.

Condition: New. In English.

Condition: New. In English.

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Condition: New. 2016. Second. paperback. . . . . .

Condition: As New. Unread book in perfect condition.

Condition: New. 2016. Second. paperback. . . . . . Books ship from the US and Ireland.

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Digital. Condition: New. A practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache SparkAbout 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 insightWho This Book Is ForThis 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 forecastingIn DetailBeyond 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 approachThis is a hands-on guide to data analysis and data processing. The concrete examples are explained with simple code and accessible data.…

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.…

PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.