Book Image

R Data Analytics Projects [Video]

By : Dipanjan Sarkar, Raghav Bali
Book Image

R Data Analytics Projects [Video]

By: Dipanjan Sarkar, Raghav Bali

Overview of this book

<p>With powerful features and packages, R empowers users to build sophisticated machine learning systems to solve real-world data problems.</p> <p>This video course takes you on a data-driven journey that starts with the very basics of R and machine learning. You will then work on three different projects to apply the concepts of machine learning. Each project will help you to understand, explore, visualize, and derive domain- and algorithm-based insights.</p> <p>By the end of this course, you will have learned to apply the concepts of machine learning to data-related problems and solve them with help of R.</p> <p>All the code and supporting files for this course are available on Github at<br /><a style="color: #fa8d11;" href="https://github.com/PacktPublishing/R-Data-Analytics-Projects" target="blank">https://github.com/PacktPublishing/R-Data-Analytics-Projects</a></p> <h1>Style and Approach</h1> <p>The course is an enticing journey that starts from the very basics and gradually picks up the pace as it unfolds. Each topic is explained with the help of a project that solves a real-world problem hands-on, thus giving you a deep insight into the world of machine learning.</p>
Table of Contents (8 chapters)
Chapter 6
Credit Risk Detection and Prediction – Predictive Analytics
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Section 6
Modeling Using Random Forests
Random forests, also known as random decision forests, are a machine learning algorithm that comes from the family of ensemble learning algorithms. - Build the initial training model with all the features - Perform predictions using this model on the test data and evaluate them - Plot some performance curves for this model