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 4
Building a Product Recommendation System
Content Locked
Section 2
Building a Recommender Engine
If we look closely, the algorithms work on input data, which is nothing but a matrix representation of the user ratings for different products. In this video, we will use matrix factorization as the basis for predicting ratings for items which the user has not yet rated. - Prepare the user-latent features matrix X and item-latent features matrix Y - Calculate the overall error - Consider users 1 and 3 as our training samples