R offers a large variety of packages and libraries for fast and accurate data analysis and visualization. As a result, its one of the most popularly used languages by data scientists and analysts, or anyone who wants to perform data analysis. This video will demonstrate how you can put to use your existing knowledge of data analysis in R to build highly efficient, end-to-end data analysis pipelines without any hassle. Youll start by building a content-based recommendation system, followed by building a project on sentiment analysis with tweets. Youll implement time-series modeling for anomaly detection and understand cluster analysis for streaming data. Youll work through projects on performing efficient market data research, building recommendation systems, and analyzing networks accurately, all provided with easy to follow code. With the help of these real-world projects, youll get a better understanding of the challenges faced when building data analysis pipelines, and see how you can overcome them without compromising on the efficiency or accuracy of your systems. The video covers some popularly used R packages such as dplyr, ggplot2, RShiny, and others, and includes tips on using them effectively. By the end of this video, youll have a better understanding of data analysis with R, and will be able to put your knowledge to practical use without any hassle. About the AuthorGopi Subramanian is a scientist and author with over 18 years of experience in the fields of data mining and machine learning. During the past decade, he has worked extensively in data mining and machine learning, solving a variety of business problems. He has 16 patent applications with the US and Indian patent offices and several publications to his credit. He is the author of Python Data Science Cookbook by Packt Publishing.
