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R: Recipes for Analysis, Visualization and Machine Learning

By Shanthi Viswanathan , Atmajitsinh Gohil , Viswa Viswanathan and 1 more
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Download this book in EPUB and PDF formats
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About this book
The R language is a powerful, open source, functional programming language. At its core, R is a statistical programming language that provides impressive tools to analyze data and create high-level graphics. This Learning Path is chock-full of recipes. Literally! It aims to excite you with awesome projects focused on analysis, visualization, and machine learning. We’ll start off with data analysis – this will show you ways to use R to generate professional analysis reports. We’ll then move on to visualizing our data – this provides you with all the guidance needed to get comfortable with data visualization with R. Finally, we’ll move into the world of machine learning – this introduces you to data classification, regression, clustering, association rule mining, and dimension reduction. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: • R Data Analysis Cookbook by Viswa Viswanathan and Shanthi Viswanathan • R Data Visualization Cookbook by Atmajitsinh Gohil • Machine Learning with R Cookbook by Yu-Wei, Chiu (David Chiu)
Publication date:
November 2016
Publisher
Packt
ISBN
9781787289598

About the Authors
  • Shanthi Viswanathan
  • Atmajitsinh Gohil
  • Viswa Viswanathan

    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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  • Yu-Wei, Chiu (David Chiu)

    Yu-Wei, Chiu (David Chiu) is the founder of LargitData (www.LargitData.com), a startup company that mainly focuses on providing big data and machine learning products. He has previously worked for Trend Micro as a software engineer, where he was responsible for building big data platforms for business intelligence and customer relationship management systems. In addition to being a start-up entrepreneur and data scientist, he specializes in using Spark and Hadoop to process big data and apply data mining techniques for data analysis. Yu-Wei is also a professional lecturer and has delivered lectures on big data and machine learning in R and Python, and given tech talks at a variety of conferences. In 2015, Yu-Wei wrote Machine Learning with R Cookbook, Packt Publishing. In 2013, Yu-Wei reviewed Bioinformatics with R Cookbook, Packt Publishing. For more information, please visit his personal website at www.ywchiu.com. **********************************Acknowledgement************************************** I have immense gratitude for my family and friends for supporting and encouraging me to complete this book. I would like to sincerely thank my mother, Ming-Yang Huang (Miranda Huang); my mentor, Man-Kwan Shan; the proofreader of this book, Brendan Fisher; Members of LargitData; Data Science Program (DSP); and other friends who have offered their support.

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R: Recipes for Analysis, Visualization and Machine Learning
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