Introducing Data Science: Big Data, Machine Learning, and more, using Python tools

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ISBN 10: 1633430030 ISBN 13: 9781633430037

Editorial: -, 2016

Usado Paperback

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Introducing Data Science: Big Data, Machine Learning, and more, using Python tools This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. N� de ref. del art�culo 7719-9781633430037

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Sinopsis:

DESCRIPTION

Data Science has become one of the hottest fields in technology. Firms worldwide are scrambling to find developers with data science skills to work on projects ranging from social media marketing to machine learning, but the prerequisite knowledge and experience for this career can seem bewildering. This book is designed to help anyone who wants to learn more about data science get started.

Introducing Data Science teaches readers how to accomplish the fundamental tasks that occupy data scientists. They’ll use the Python language and common Python libraries as they experience firsthand the challenges of dealing with data at scale. They’ll discover how Python allows them to gain insights from huge data sets that need to be stored on multiple machines, or for data moving at such speed no single machine can handle it. After reading this book, readers will have a solid foundation to consider a career in data science.

KEY SELLING POINTS

Master big data with Python and become a data scientist

How to use data science in a big data world

Gain hands on experience with the most common Python data science libraries

AUDIENCE

This book assumes readers (software engineers, business intelligence reporters, database moderators, statisticians, web developers, anyone interested in Big Data) are comfortable reading code in Python or a similar language, such as C, Ruby, or JavaScript. No prior experience with data science is required.

ABOUT THE TECHNOLOGY

At its core, data science is a set of concepts and techniques for extracting meaning and clarity from enormous stored data sets or fast-moving data streams. Data scientists write programs to interpret these data. The Python programming language is a favorite tool of data scientists because it's easy to read and write, and it provides several high-value libraries that simplify core tasks like statistics, machine learning algorithms, and mathematics.

Acerca del autor:

Davy Cielen is one of the founders and managing partners of Optimately where he focuses on leading and developing data science projects and solutions in various sectors and closely follows new developments in data science. Before Optimately he worked on data science and big data projects at a major retailer.

Arno Meysman is one of the founders and managing partners of Optimately where he focuses on leading and developing data science projects and solutions in various sectors and closely follows new developments in data science. Before Optimately he worked on data science and big data projects at a major retailer. Apart from data science he is also into data visualisation and generally "Creating data-driven things that are smart, interactive and pretty".

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Detalles bibliogr�ficos

T�tulo: Introducing Data Science: Big Data, Machine ...
Editorial: -
A�o de publicaci�n: 2016
Encuadernaci�n: Paperback
Condici�n: Very Good

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Davy Cielen; Arno Meysman; Mohamed Ali

Publicado por Manning Publications, 2016

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Davy Cielen, Arno Meysman, Mohamed Ali

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Introducing Data Science: Big Data, Machine Learning, and more, using Python tools

Davy Cielen, Arno Meysman, Mohamed Ali

Publicado por Manning Publications, 2016

ISBN 10: 1633430030 ISBN 13: 9781633430037

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Cielen, David,Meysman, Arno

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Davy Cielen, Davy, Arno Meysman, Arno, Mohamed Ali, Mohamed

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Davy Cielen, Davy, Arno Meysman, Arno, Mohamed Ali, Mohamed

Publicado por Manning Publications Co. LLC, 2016

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