Books are open doors to the unimagined worlds which is unique to every person. It is more than just a hobby for many. There are many among us who prefer to spend more time with books than anything else. Here we explore a big database of books. Books of different genres, from thousands of authors. In this challenge, we are required to use the dataset to build a Machine Learning model to predict the price of books based on a given set of features.
Size of training set: 6237 records Size of test set: 1560 records
FEATURES:
1.Title: The title of the book
2.Author: The author(s) of the book.
3.Edition: The edition of the book eg (Paperback,– Import, 26 Apr 2018)
4.Reviews: The customer reviews about the book
5.Ratings: The customer ratings of the book
6.Synopsis: The synopsis of the book
7.Genre: The genre the book belongs to
8.BookCategory: The department the book is usually available at.
9.Price: The price of the book (Target variable)