Introduction

In todays world, a user is often faced with multiple choices and often does not have the intrest to browse through the options.

We will look at the concept of Recommendation system using Goodreads book dataset

The goodreads book dataset contains six million ratings for 10000 most popular books.The dataset contains, ratings for the books by users, the books marked to-read by users, metadata of the book and tags associated with abook
Ratings are between 1-5. Both book IDs and user IDs are contiguous. For books, they are 1-10000, for users, 1-53424.

The link to the dataset can be found at :

https://github.com/zygmuntz/goodbooks-10k/releases

Importing Libraries

import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
pd.set_option('display.max_colwidth', -1)

import os

input_path="../data/goodbooks-10k/"

os.listdir(input_path)

['book_tags.csv',
 'LICENSE',
 'tags.csv',
 'README.md',
 'ratings.csv',
 'to_read.csv',
 'books.csv']