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This project was run in DataBricks using spark to analyze the recent news in 'cancer' for sentiment evaluation. The goal of this project is to practice traditional NLP like tokenization, stopwords, CV and TF-IDF, N-grams. Also, this project applied tools like AWS S3, athena, QuickSight etc. to address big data.

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Cancer_sentiment_ML.dbc		Cancer_sentiment_ML.dbc
Cancer_sentiment_analysis.pdf		Cancer_sentiment_analysis.pdf
README.md		README.md

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Cancer-Sentiment-Analysis

Summary

This project aims to practice NLP using spark and process bigdata using Amazon Web Service.
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This project was run in DataBricks using spark to analyze the recent news in 'cancer' for sentiment evaluation. The goal of this project is to practice traditional NLP like tokenization, stopwords, CV and TF-IDF, N-grams. Also, this project applied tools like AWS S3, athena, QuickSight etc. to address big data.

sentiment-analysis athena bigdata ngrams multiclass-classification quicksight

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