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
andreview_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