Book Image

Advanced Analytics with R and Tableau

By : Ruben Oliva Ramos, Jen Stirrup, Roberto Rösler
Book Image

Advanced Analytics with R and Tableau

By: Ruben Oliva Ramos, Jen Stirrup, Roberto Rösler

Overview of this book

Tableau and R offer accessible analytics by allowing a combination of easy-to-use data visualization along with industry-standard, robust statistical computation. Moving from data visualization into deeper, more advanced analytics? This book will intensify data skills for data viz-savvy users who want to move into analytics and data science in order to enhance their businesses by harnessing the analytical power of R and the stunning visualization capabilities of Tableau. Readers will come across a wide range of machine learning algorithms and learn how descriptive, prescriptive, predictive, and visually appealing analytical solutions can be designed with R and Tableau. In order to maximize learning, hands-on examples will ease the transition from being a data-savvy user to a data analyst using sound statistical tools to perform advanced analytics. By the end of this book, you will get to grips with advanced calculations in R and Tableau for analytics and prediction with the help of use cases and hands-on examples.
Table of Contents (16 chapters)
Advanced Analytics with R and Tableau
About the Authors
About the Reviewers
Customer Feedback

What are neural networks?

Neural networks are one of the most interesting machine learning models. Neural networks are inspired by the structures of the brain. Neural networks are algorithms that mimic the functioning of the brain. They are unsupervised algorithms, which means that we do not always know what the outputs should be.

Neural networks have layers, which can be categorized into the following:

  • Input

  • Middle

  • Output layers

The input layer consumes the data, and the output layer represents the result. The middle layer represents the part of the algorithm that indicates how the input layer gets to the output layer.

Different types of neural networks

The simplest type of neural network is known as a Feedforward Neural Network. It feeds information in one direction only, from the front to the back. This type of network is also known as a perceptron. The following figure illustrates a perceptron:

Neural network training process

Neural networks can also feed information back down through the layers...