Sentiment Analysis Application

This project is a sentiment analysis application that analyzes text input and determines whether the sentiment is positive or negative. The application uses a deep learning model trained on text data, with results stored in MongoDB.

Table of Contents

• Introduction
• Features
• System Requirements
• Installation
• Usage
• Results Storage in MongoDB
• Testing
• Deployment

Introduction

This application is built using Flask, TensorFlow, and MongoDB. It allows users to input text, analyzes the sentiment, and stores the analysis results in MongoDB for future reference.

Features

• Sentiment analysis using a trained LSTM model.
• User-friendly web interface.
• Results storage in MongoDB.

System Requirements

• Python 3.7+
• TensorFlow 2.x
• Flask
• MongoDB

Installation

1. Clone the Repository

git clone https://github.com/username/repository.git
cd repository

2. Navigate to the project directory:

cd your-repo-name

3. Install the required dependencies:

pip install -r requirements.txt

Execution

Train the model

python train_model.py

Run the application

python main.py