Book Image

R Deep Learning Cookbook

By : PKS Prakash, Achyutuni Sri Krishna Rao
Book Image

R Deep Learning Cookbook

By: PKS Prakash, Achyutuni Sri Krishna Rao

Overview of this book

Deep Learning is the next big thing. It is a part of machine learning. It's favorable results in applications with huge and complex data is remarkable. Simultaneously, R programming language is very popular amongst the data miners and statisticians. This book will help you to get through the problems that you face during the execution of different tasks and Understand hacks in deep learning, neural networks, and advanced machine learning techniques. It will also take you through complex deep learning algorithms and various deep learning packages and libraries in R. It will be starting with different packages in Deep Learning to neural networks and structures. You will also encounter the applications in text mining and processing along with a comparison between CPU and GPU performance. By the end of the book, you will have a logical understanding of Deep learning and different deep learning packages to have the most appropriate solutions for your problems.
Table of Contents (17 chapters)
Title Page
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Setting up a Restricted Boltzmann machine for Collaborative Filtering


In this recipe, you will learn how to build a collaborative-filtering-based recommendation system using an RBM. Here, for every user, the RBM tries to identify similar users based on their past behavior of rating various items, and then tries to recommend the next best item.

Getting ready

In this recipe, we will use the movielens dataset from the Grouplens research organization. The datasets (movies.dat and ratings.dat) can be downloaded from the following link. Movies.dat contains information of 3,883 movies and Ratings.dat contains information of 1,000,209 user ratings for these movies. The ratings range from 1 to 5, with 5 being the highest.

http://files.grouplens.org/datasets/movielens/ml-1m.zip

How to do it...

This recipe covers the steps for setting up collaborative filtering using an RBM.

  1. Read the movies.dat datasets in R:
txt <- readLines("movies.dat", encoding = "latin1") 
txt_split <- lapply(strsplit(txt, "::...