Restaurant Rating Prediction, Recommendation and Analysis

Internship at Cognifyz technologies

  This project focuses on building a machine learning system that predicts restaurant ratings, recommends restaurants
  based on user preferences,and analyzes cuisine trends.It using multiple algorithms and data processing techniques to 
  deliver insights predictions.

Level 1

Steps:

Preprocess the dataset by handling missing values, encoding categorical variables, and splitting the data into training 
and testing sets.
Select a regression algorithm (e.g., linear regression, decision tree regression) and train it on the training data.
Evaluate the model's performance using appropriate regression metrics (e.g., mean squared error, R-squared) on the 
testing data.
Interpret the model's results and analyze the most influential features affecting restaurant ratings.

Level 2

Steps

Preprocess the dataset by handling missing values and encoding categorical variables.
Determine the criteria for restaurant recommendations (e.g., cuisine preference, price range).
Implement a content-based filtering approach where users are recommended restaurants similar to their preferred criteria.
Test the recommendation system by providing sample user preferences and evaluating the quality of recommendations.

Level 3

Steps

Preprocess the dataset by handling missing values and encoding categorical variables.
Split the data into training and testing sets.
Select a classification algorithm (e.g., logistic regression, random forest) and train it on the training data.
Evaluate the model's performance using appropriate classification metrics (e.g., accuracy, precision, recall) on the testing data.
Analyze the model's performance across different cuisines and identify any challenges or biases.

Project Structure

├── Dataset.csv                        # Raw dataset containing restaurant details
├── Restaurant_rating_predictions.ipynb # Rating prediction models and evaluation
├── Cuisine_classification.ipynb       # Cuisine classification and model training
├── EDA.ipynb                           # Exploratory data analysis
├── README.md                           # Project documentation

How to Run

git clone:
https://github.com/Shreyaskulkarni56/Restaurant-Rating-and-Recommendation-System.git

Author

Shreyas Kulkarni
LinkedIn :shreyas-kulkarni-7934aa254  
GitHub : Shreyaskulkarni56