Book Image

R Data Analysis Projects

Book Image

R Data Analysis Projects

Overview of this book

R offers a large variety of packages and libraries for fast and accurate data analysis and visualization. As a result, it’s one of the most popularly used languages by data scientists and analysts, or anyone who wants to perform data analysis. This book 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. You’ll start by building a content-based recommendation system, followed by building a project on sentiment analysis with tweets. You’ll implement time-series modeling for anomaly detection, and understand cluster analysis of streaming data. You’ll work through projects on performing efficient market data research, building recommendation systems, and analyzing networks accurately, all provided with easy to follow codes. With the help of these real-world projects, you’ll 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 book 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 book, you’ll have a better understanding of data analysis with R, and be able to put your knowledge to practical use without any hassle.
Table of Contents (15 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Deep neural networks


Neural networks are extremely popular today, thanks to major research advancement over the last 10 years. The result of this research has culminated in deep learning algorithms and architecture. Big technology giants such as Google, Facebook, and Microsoft are heavily investing in deep learning network research. Complex neural networks powered by deep learning are considered state of the art in AI and machine learning. We see them being used in everyday life. For example, Google's image search is powered by deep learning. Google Translate is another application powered by deep learning today. The field of computer vision has made several advancements thanks to deep learning.

The following diagram is a typical neural network, commonly called a multi-layer perceptron:

This network architecture has a single hidden layer with two nodes. The output layer is activated by a softmax function. This network is built for a classification task. The hidden layer can be activated by...