A recommendation system is typically used by product-oriented companies. Some of the big eCommerce websites like Amazon and Myntra continue to update their recommendation systems to provide a better user experience. In this article, I will introduce you to 2 recommendation system projects using Python, which will help you understand how to create a recommendation system for any kind of product or service.
Recommendation System Projects using Python
recommendation systems are based on two major approaches:
- Collaborative Filtering
- Content-Based Filtering
Some companies use both of these methods, while some companies’ recommendation systems are based on a single approach. Below are some of the best recommendation system data science projects solved and explained using Python.
Collaborative Filtering (Hotel Recommendation)
A hotel recommendation system aims to predict which hotel a user is most likely to choose from among all hotels. So to build this type of system which will help the user to book the best hotel out of all the other hotels. We can do this using customer reviews.
For example, suppose you want to go on a business trip, so the hotel recommendation system should show you the hotels that other customers have rated best for business travel. It is therefore also our approach to build a recommendation system based on customer reviews and ratings.
Content-Based Filtering (Movie Recommendation)
A recommendation system based on content-based filtering provides recommendations to the user by analyzing the description of the content that has been rated by the user. In this method, the algorithm is trained to understand the context of the content and find similarities in other content to recommend the same class of content to a particular user.
Here you will learn how to create a movie recommendation system using content-based filtering.
So these two projects will teach you a lot about how to create recommendation systems for any type of product. I hope you liked this article on recommendation system projects using Python. Feel free to ask your valuable questions in the comments section below.