Sentiment Analysis Model

This project is a sentiment analysis model that can classify text as positive or negative. The model is trained on a dataset of movie reviews and can be used to classify the sentiment of any text.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

• Python 3.6 or higher
• scikit-learn
• pandas
• numpy
• pickle

Installing

Clone the repository and install the dependencies using pip:

git clone https://github.com/Sultan-aj/Sentiment-Analysis.git
pip install -r requirements.txt

Running the model

To use the model, you can use the provided predict.py script to classify the sentiment of a single text.

1. Open the predict.py script in your text editor.
2. Locate the following line:

with open("insert_your_file_path_here", "r") as f:

3. Replace 'insert_your_file_path_here' with the path to your text file.

with open("path/to/text_file.txt", "r") as f:

4. Save the changes to the predict.py script.
5. Run the script by typing the following command in your terminal:

python predict.py

Built With

• Scikit-learn - The machine learning library used
• Pandas - Data manipulation and analysis
• Numpy - Scientific computing with Python
• Pickle - Serialization of the trained model

Author

• Sultan.aj - https://github.com/Sultan-aj

License

This project is licensed under the MIT License - see the LICENSE.md file for details.