Restaurant Recommendation System Depend on the frame of mind

Introduction

So here is another project idea on data mining or data analysistechnology. It will definitely help to improve your knowledge in data mining field. It analyses the data and uses it to find a similar pattern for prediction and recommendation. So in this article, we will introduce the Restaurant Recommendation System depend on the frame of mind. Data mining system learns from examples of the data that how to partition or classify the data. It helps to discover hidden patterns and insights. If you are interested then Skyfi Labs provides you data mining course too. Check our website for more information.

Project Description

So this article is all about the Restaurant Recommendation System depend on the frame of mind. We will see the basic guidelines for the implementation of the project. The article is helpful for second-year students as their minor academic project. The project focuses on different kinds of mood-wise restaurant recommendations. For example, if the person is happy then he/she will prefer junk food like pizza, burger, etc. If the mood is angry or sad then the person will prefer sweet any more. The article gives back end implementation guidelines for the project.

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1. Data Analytics using R

Technologies used

Data Mining

Data Analysis 

Implementation Guidelines

1. In this project, we are using two datasets. First one is Swiggy restaurants in Mumbai city. The second one is the food choices of the persons which are real-time datasets. It contains food choice of the persons based on their frame of mind.
2. We have to import some basic python libraries usually used like numpy, pandas, seaborn, matplotlib etc. Also, we need to import some packages like NLTK and collection. Then we have to import the Swiggy restaurants dataset for analysis.
3. There are different stages in data mining, so first one is data cleaning. We have to remove all the Null entries in the dataset.
4. After that, we will do data aggregation to find the most famous food in the city. Using matplotlib you can plot a graph for that for better understanding.
5. So this is all about the first dataset.
6. Now coming towards the second dataset which is based on the survey of the food choices of persons. 
7. There are different attributes but we are focusing on the comfort_food_type which contains the name of different foods depending upon comfort_food_reasons which consist of different moods. Maybe there are different names of attributes for these so take a look at it. So there are different moods like anger, happy, sad which consist of different_food_reason, and another column consists of the types of food in that particular mood.
8. This data is also not clean so we are using Natural language processing, we will lemmatize the data with the wordnet lemmatizer of NLTK.
9. Now create a function in which you have to lemmatize the data. It will display the types of foods according to the entered entity(mood).
10. The output will get compared with the first dataset which is for Swiggy restaurants. In simple words, the output of the second dataset get compared with the first dataset and suggest the restaurant which is famous for such kind of cuisines.

So this is a basic idea for the Restaurant Recommendation System depends on the frame of mind project. You can create a web app for a better experience. For that, you need to learn Django framework. Skyfi Labs provides a complete Django course for the students. So you can enroll and keep improving yourself. 

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• Python
• Machine Learning

• Data Mining

Restaurant Recommendation System Depend on the frame of mind