DataScience_FinalProject_AmazonFineFoodSentimentAnalysis

Team11_FinaProject_Report

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Purpose of this project is to achieve sentiment classification of amazon fine food reviews Below are the steps involved in it:

• Data Extraction and Conversion
• Cleaning and pre-processing
• Data Exploratory analysis (using python and Power BI)
• Sentiment classification and analysis
• Luigi Pipeline
• Dockerization
• Creation of Rest API using Microsoft Azure ML Studio
• UI deployment

Following files are present

• Team11_FinaProject_Report.docx It contains detailed report for project

• team11_finalproject_presentation.pptx It contains presnetation for a final project

• Data download data_download.ipynb

• Data conversion data_conversion.ipynb

• Exploratory analysis AmazonExploratoryAnalysis.R and

• Classification of review and sentiment analysis review-classification.ipynb and review_preprocessing-feature-extraction_classification.ipynb

• Top worst and good reviews top_good_worst_reviews.R

• Luigi_docker folder contains script finefoods_luigi.py and Dockerfile

• luigi folder contains script for tasks

• WebApplication8 folder code related to UI and service deployment