Sentiment Analysis Pipeline

This project performs sentiment analysis on tweets using machine learning models. The pipeline includes data loading, preprocessing, model training, evaluation, and result storage in an SQLite database.

Project Structure

│── data/                          # Raw and processed data
│   ├── raw/                       # Original Excel files
│   ├── processed/                 # Preprocessed data
│── database/                      # SQLite database and schema
│── logs/                          # Logs for debugging
│   ├── pipeline.log               # Log file capturing pipeline execution
│── notebooks/                     # Jupyter notebooks for analysis
│── src/                           # Source code
│   ├── config.py                  # Configuration settings
│   ├── load_data.py               # Load tweets from Excel
│   ├── preprocess.py              # Preprocessing functions
│   ├── make_model.py              # Model training & prediction
│── scripts/                       # Scripts for execution
│   ├── run_pipeline.py            # End-to-end execution
│── requirements.txt               # Dependencies
│── README.md                      # Project documentation