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R Data Analysis Cookbook. Customizable R Recipes for data mining, data visualization and time series analysis - Second Edition

Język publikacji: angielskim
Autorzy:
Kuntal Ganguly, Shanthi Viswanathan, Viswa Viswanathan
R Data Analysis Cookbook. Customizable R Recipes for data mining, data visualization and time series analysis - Second Edition Kuntal Ganguly, Shanthi Viswanathan, Viswa Viswanathan - okladka książki

R Data Analysis Cookbook. Customizable R Recipes for data mining, data visualization and time series analysis - Second Edition Kuntal Ganguly, Shanthi Viswanathan, Viswa Viswanathan - okladka książki

Wydawnictwo:
Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
560
Dostępne formaty:
     PDF
     ePub
     Mobi

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Do przechowalni

Data analytics with R has emerged as a very important focus for organizations of all kinds. R enables even those with only an intuitive grasp of the underlying concepts, without a deep mathematical background, to unleash powerful and detailed examinations of their data.

This book will show you how you can put your data analysis skills in R to practical use, with recipes catering to the basic as well as advanced data analysis tasks. Right from acquiring your data and preparing it for analysis to the more complex data analysis techniques, the book will show you how you can implement each technique in the best possible manner. You will also visualize your data using the popular R packages like ggplot2 and gain hidden insights from it. Starting with implementing the basic data analysis concepts like handling your data to creating basic plots, you will master the more advanced data analysis techniques like performing cluster analysis, and generating effective analysis reports and visualizations. Throughout the book, you will get to know the common problems and obstacles you might encounter while implementing each of the data analysis techniques in R, with ways to overcoming them in the easiest possible way.

By the end of this book, you will have all the knowledge you need to become an expert in data analysis with R, and put your skills to test in real-world scenarios.

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O autorach książki

Kuntal Ganguly is a big data analytics engineer focused on building large-scale, data-driven systems using big data frameworks and machine learning. He has around 7 years experience of building big data and machine learning applications. Kuntal provides solutions to cloud customers in building real-time analytics systems using managed cloud services and open source Hadoop ecosystem technologies such as Spark, Kafka, Storm, Solr, and so on, along with machine learning and deep learning frameworks. Kuntal enjoys hands-on software development and has single-handedly conceived, architected, developed, and deployed several large-scale distributed applications. He is a machine learning and deep learning practitioner and is very passionate about building intelligent applications.
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Viswa Viswanathan is an associate professor of Computing and Decision Sciences at the Stillman School of Business in Seton Hall University. After completing his PhD in Artificial Intelligence, Viswa spent a decade in academia and then switched to a leadership position in the software industry for another decade during which he worked for Infosys, Igate, and Starbase. He embraced academia once again in 2001.
Viswa has taught extensively in fields ranging from operations research, computer science, software engineering, management information systems, and enterprise systems. In addition to university teaching, Viswa has conducted training programs for industry professionals and has written several peer-reviewed research publications in journals such as Operations Research, IEEE Software, Computers and Industrial Engineering, and International Journal of Artificial Intelligence in Education. He has authored a book titled Data Analytics with R:A hands-on approach.
Viswa thoroughly enjoys hands-on software development and has single-handedly conceived, architected, developed, and deployed several web-based applications.
Apart from his deep interest in technical fields such as data analytics, artificial intelligence, computer science, and software engineering, Viswa harbors a deep interest in education with special emphasis on the roots of learning and methods to foster deeper learning. He has done research in this area and hopes to pursue the subject further.
Viswa would like to express deep gratitude to professors Amitava Bagchi and Anup Sen, who were inspirational forces during his early research career. He is also grateful to several extremely intelligent colleagues, notable among them being Rajesh Venkatesh, Dan Richner, and Sriram Bala, who significantly shaped his thinking. His aunt, Analdavalli; his sister, Sankari; and his wife, Shanthi, taught him much about hard work, and even the little he has absorbed has helped him immensely. His sons, Nitin and Siddarth, have helped with numerous insightful comments on various topics.

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