Restaurant Recommendation System using Machine Learning
In this article we are going to discuss about the Restaurant Recommendation System. it is an application that recommends similar restaurants to a customer according to the customer’s taste. We will learn how to build a restaurant recommendation system. This article will take you through how to build a restaurant recommendation system using Machine Learning.
You can download the dataset from here.
Now we will import Python libraries and the dataset we need for this task and check the top 5 rows of our dataset:
We will be selecting two columns from the dataset which we need for the rest of the task (Name, Type):
Now, we will check whether we have null values in our dataset or not.
The type of restaurant is a valuable feature in the data to build a recommendation system. The type column here represents the category of restaurants. For example, if a customer likes vegetarian-friendly restaurants, he will only look at the recommendations if they are vegetarian friendly too. So, I will use the Type column as the feature to recommend similar restaurants to the customer:
Now I will set the name of the restaurant as an index so that we can find similar restaurants by giving the name of the restaurant as an input:
Now we will write a function to recommend similar restaurants:
So, this is how to build a restaurant recommender system using the machine learning. I hope you liked this article on building a restaurant recommender system using Machine Learning.