This repository contains an implementation of sentiment analysis on the IMDb dataset using machine learning techniques, as demonstrated in the YouTube video "Sentiment Analysis on IMDb Dataset | Kaggle Challenge Uncovered!". The entire analysis is contained in a single Jupyter Notebook, sentimentAnalysis.ipynb.
To run this project, you'll need the following software installed on your local machine:
- Python 3.7 or higher
- Jupyter Notebook
- Clone the repository:
git clone https://github.com/aadyanthaya/IMDBSentimentalAnalysis.git- Change to the project directory:
cd sentiment-analysis-imdb- Start Jupyter Notebook:
jupyter notebook- Open the sentimentAnalysis.ipynb notebook in your web browser and follow the steps to run the code.
The sentimentAnalysis.ipynb notebook includes the following sections:
- Introduction
- Data Loading and Exploration
- Data Cleaning and Preprocessing
- Feature Extraction
- Model Selection and Training
- Model Evaluation and Testing
- Conclusion and Future Work
If you have any suggestions for improvements or find any bugs, feel free to create an issue or submit a pull request.
If you have any suggestions for improvements or find any bugs, feel free to create an issue or submit a pull request.
This project is licensed under the MIT License.
- IMDb dataset provided by Kaggle
- Natural Language Processing libraries and resources
- Inspiration and guidance from the data science community