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https://github.com/badranalyst/restaurant-reviews-sentiment-analysis-nlp-case-study
This project analyzes restaurant reviews using Natural Language Processing (NLP) for sentiment analysis. It covers data exploration, pre-processing (NLTK text cleaning), model building, prediction, and deployment. The goal is to predict sentiment from reviews using Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn.
https://github.com/badranalyst/restaurant-reviews-sentiment-analysis-nlp-case-study
data-analysis data-science eda exploratory-data-analysis matplotlib-pyplot model model-building numpy pandas pre-processing predictive-modeling python seaborn
Last synced: 9 days ago
JSON representation
This project analyzes restaurant reviews using Natural Language Processing (NLP) for sentiment analysis. It covers data exploration, pre-processing (NLTK text cleaning), model building, prediction, and deployment. The goal is to predict sentiment from reviews using Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn.
- Host: GitHub
- URL: https://github.com/badranalyst/restaurant-reviews-sentiment-analysis-nlp-case-study
- Owner: BadrAnalyst
- Created: 2024-12-26T11:57:39.000Z (13 days ago)
- Default Branch: main
- Last Pushed: 2024-12-26T11:58:44.000Z (13 days ago)
- Last Synced: 2024-12-26T12:28:20.704Z (13 days ago)
- Topics: data-analysis, data-science, eda, exploratory-data-analysis, matplotlib-pyplot, model, model-building, numpy, pandas, pre-processing, predictive-modeling, python, seaborn
- Language: Jupyter Notebook
- Homepage:
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Restaurant-Reviews-Sentiment-Analysis-NLP-Case-Study
This project analyzes restaurant reviews using Natural Language Processing (NLP) for sentiment analysis. It covers data exploration, pre-processing (NLTK text cleaning), model building, prediction, and deployment. The goal is to predict sentiment from reviews using Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn.