Building the revised approach

In this iteration, we will be building the recommendation engine using a statistical concept called correlation. We will be looking at how users' activities and choices are correlated to one another. We try to find out the pattern from the users' activities and behavior on the e-commerce platform.

Here, we will be using the Book-Crossing dataset. One of the critical parameters for building the recommendation system is the book rating attribute. I will explain the concepts along with the implementation part, so it will be easy for you to understand.

Implementing the revised approach

In order to implement the revised approach, we will need to perform the following steps. You can refer to the code on GitHub at: https://github.com/jalajthanaki/Book_recommendation_system/blob/master/correlation_based_recommendation_system.ipynb

1. Loading the dataset

2. Exploratory Data Analysis (EDA) of book-rating datafile

3. Exploring the book datafile

4. EDA of user datafile

5. Implementing the...