Zomato-Restaurant-Clustering-and-Sentiment-Analysis

• Analyze the textual data, categorized restaurants based on features such as cuisine, cost, location, and user ratings using clustering techniques.
• Conducted sentiment analysis on user reviews using NLP and discovered topics of interest.
• The findings of the analysis can be used by restaurant owners and managers to improve their offerings and customer experience, and by food industry analysts to gain a deeper understanding of market trends and consumer behavior.
• It will enhance the customer experience by up to 90%. Helps to grow business by up to 80 %.

Libraries Used:

Numpy
Pandas
Matpllotlib
Seaborn
sklearn
xgboost
warnings

Machine Learning Models Implimented:

Latent Direclet Allowcation
Negative and Positive sentiment Analysis With Polyrity
K-means Clustering