CNN-based model to realize aspect extraction of restaurant reviews based on pre-trained word embeddings and part-of-speech tagging

Project - Data Processing and Analysis in Python Course

writing style transfer using cycle gan

🍕Recommend new restaurants to Yelp users, using ratings predicted from reviews.

Code for GenAug: Data Augmentation for Finetuning Text Generators.

Analyzing yelp reviews using topic modelling and aspect mining

Where to eat in Las Vegas: Topic Models, Networks, & Yelp Reviews

Sentiment analysis with YELP Reviews and Transformers.

Codes for the experiments in our EMNLP 2021 paper "Open Aspect Target Sentiment Classification with Natural Language Prompts"

Analyzing yelp dataset ==> https://www.yelp.com/dataset_challenge

Recurrent Capsule Network for Text Classification

Topic modeling and sentiment analysis on Yelp's reviews using NLTK, sklearn, gesim, LdaMallet, and vaderSentiment libraries.

DL, ML, and Rule based approaches for Sentiment analysis

Project for the Big Data Course as part of 5th semester.

Application that predicts the number of stars that of a Yelp Review in realtime as a reviewer types it. Runs as a microservice-based application using Node.js, Python, and Docker. Displays results from Google Natural Language API and a custom trained classification models.

Our goal in this group project is to apply NLP and other features from Yelp reviews into a model that outputs a new 5-star-rating, so that there is less discrepancy between reviews and star ratings. In order to make our model more robust, we will also incorporate new user star-ratings based on reviews read (meaning that someone who did not write…

Big Data coursework using Hadoop/Spark, and concepts of mapreduce, graph theory, text mining, machine learning, etc.

A minimal Flask API to generate random lunch reviews

Enrolled in a Thinkful course on Data Science

This is my data mining project for CS573 (dataset is from Kaggle: https://www.kaggle.com/yelp-dataset/yelp-dataset)