Sentiment Analysis Project : This project implements a Sentiment Analysis tool using Python, Flask, and machine learning models. The application allows users to input text and analyze its sentiment, classifying it as positive, negative, or neutral. Features:

Input text and analyze sentiment. User-friendly web interface for easy interaction. Real-time sentiment analysis using machine learning. Project Structure: Sentiment-Analysis-Project/ ├── app.py # Main Flask application file ├── .gitignore # Git ignore file to exclude unnecessary files ├── requirements.txt # Python dependencies ├── README.md # Project documentation ├── static/ # Folder for static files (CSS, JS) │ ├── css/ │ └── scripts.js ├── src/ # Source code for data collection, preprocessing, and analysis │ ├── data_collection.py │ ├── data_preprocessing.py │ └── sentiment_analysis.py ├── templates/ # HTML files for the user interface │ └── index.html └── tests/ # Unit tests └── test_sentiment_analysis.py

Prerequisites: Before running the application, ensure that you have the following installed on your system:

Python 3.x pip (Python package installer)

Setting Up the Project: Step 1: Clone the Repository Clone the project to your local machine using the following command: git clone https://github.com/YourUsername/Sentiment-Analysis-Project.git cd Sentiment-Analysis-Project

Step 2: Set Up the Virtual Environment: Create a virtual environment for the project: python -m venv .venv

Step 3: Activate the Virtual Environment Activate the virtual environment using the appropriate command for your operating system: Windows: .\venv\Scripts\activate macOS/Linux: source venv/bin/activate

Step 4: Install Dependencies Install the necessary Python packages by running: pip install -r requirements.txt

Running the Application To start the application, run the following command: python app.py

After running the command, the application will be hosted locally. Open your browser and go to the following URL to access the application: http://127.0.0.1:5000

Sample Output The application will display a text box where you can input text for sentiment analysis. After clicking "Analyze," the sentiment (positive, negative, or neutral) of the entered text will be displayed.

Testing the Application You can test the functionality of the sentiment analysis by running the unit tests: pytest

Contribution If you'd like to contribute to this project, feel free to fork the repository, make your changes, and create a pull request. Contributions are always welcome!

License This project is open source and available under the MIT License.