Working with the Yelp Dataset in Azure SQL and SQL Server
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Updated
Mar 3, 2021 - TSQL
Working with the Yelp Dataset in Azure SQL and SQL Server
Analyzing yelp reviews using topic modelling and aspect mining
This repo contains the Yelp dataset challenge implementation for predicting the business category and recommending food items based on the 1.6M reviews.
Analyzing yelp dataset ==> https://www.yelp.com/dataset_challenge
Contains Python scripts to import and model the Yelp challenge dataset into Neo4j respectively.
This is an attempt to predict rush hours and help the businesses to maximize their profits.
A Python 3 script to normalize the Yelp challenge dataset to its core attributes, perform feature selection, generate a subset of the dataset, and output to CSV.
Analysis of Yelp Json dataset and drawing useful information using MongoDB
Text Mining on Yelp Challenge Dataset
Final project for a big data course ( CS 4301 ). This was done with another team member - @AkshayRameshAppDEV
Analysing Yelp reviews and classifying them as Food Relevant/Irrelevant
Contains the GSQL scripts and TigerGraph solution to import and model the Yelp challenge dataset into TigerGraph respectively.
yelp dataset challenge round 12 (NLP)
Yelp Data Challenge 10
Analysis of Yelp Json dataset and drawing useful information using MySQL
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