https://github.com/tanyakuznetsova/imdb_sentiment_analysis

The project classifies 50,000 IMDB movie reviews into positive or negative sentiments using machine learning techniques
https://github.com/tanyakuznetsova/imdb_sentiment_analysis

logistic-regression sentiment-analysis sentiment-classification

Last synced: about 2 months ago
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The project classifies 50,000 IMDB movie reviews into positive or negative sentiments using machine learning techniques

• Host: GitHub
• URL: https://github.com/tanyakuznetsova/imdb_sentiment_analysis
• Owner: tanyakuznetsova
• Created: 2023-06-22T18:33:51.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-05-15T18:09:30.000Z (8 months ago)
• Last Synced: 2024-05-16T06:22:38.600Z (8 months ago)
• Topics: logistic-regression, sentiment-analysis, sentiment-classification
• Language: Jupyter Notebook
• Homepage:
• Size: 2.66 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## Sentiment Analysis of 50,000 IMDB Movies 

This notebook explores the power of sentiment analysis that classifies 50,000 IMDB movies into positive or negative sentiments. 

Leveraging cutting-edge natural language processing techniques, this project provides insights into the emotional tone of each movie review, helping gauge audience reactions with surprising accuracy.

## Key Features

Comprehensive Dataset: I analyze a diverse range of 50,000 IMDB movie reviews, providing a comprehensive overview of audience sentiments. 

But first, I dive deeper into exploring and representing the data visually and with key metrics.

After that, I perform a sentiment analysis and compare several algorithms against a fine-tuned logistic regression.

Follow along as we explore the emotional landscape of movie reviews and uncover insights of entertainment analysis.