Project done under the course Machine Learning A-Z™: Hands-On Python & R In Data Science. This project reads a TSV file, cleans the restaurant reviews, generates a bag-of-words model and uses a classifier which tells whether the review is a positive one or a negative one.

Docker supported restaurant crawlers.

A repo to query Zomato API

Build a Flask web application to help users retrieve key restaurant information and feature-based reviews (generated by applying market-basket model – Apriori algorithm and NLP on user reviews).

NLP - NLTK - Restaurant review analysis

cat🐈: the repo for the paper "Embarrassingly Simple Unsupervised Aspect extraction"

This project performs sentiment analysis on restaurant reviews using Natural Language Processing (NLP) techniques in Python. It utilizes various machine learning algorithms, including Multinomial Naive Bayes, Bernoulli Naive Bayes, and Logistic Regression, to classify reviews as liked or disliked.

This is the project that I created while working at TCS iON. The model is deployed on Heroku using Flask.

Restaurant Review Analysis. "Thrilled to unveil my latest project on Streamlit - a cutting-edge restaurant review ML model 🍽️🔍 Using innovative AI technology, share your feedback and predict to model. Join me on LinkedIn to explore the future of culinary exploration! #AI #MachineLearning #Streamlit #RestaurantReviews".

Restaurant Review Analysis. "Thrilled to unveil my latest project on Streamlit - a cutting-edge restaurant review ML model 🍽️🔍 Using innovative AI technology, share your feedback and predict to model. Join me on LinkedIn to explore the future of culinary exploration! #AI #MachineLearning #Streamlit #RestaurantReviews" .

Insight Platter: A comprehensive platform offering actionable insights from restaurant reviews through web scraping, sentiment analysis, and data visualization.

Local RAG chatbot that answers questions about pizza restaurant reviews using LangChain, Ollama, and Chroma vector database - fully offline with no API dependencies