Advanced Sentiment Analysis Streamlit App

Project Overview

This application provides users with a comprehensive interface to analyze and compare multiple sentiment analysis models, making it ideal for data scientists, NLP researchers, and machine learning enthusiasts.

The Advanced Sentiment Analysis Streamlit App is a powerful tool that leverages multiple machine learning and deep learning models to perform sentiment analysis on movie reviews. Built with Python and Streamlit, it offers a clean, intuitive web interface for comparing the performance of various models including Logistic Regression, Naive Bayes, Random Forest, Support Vector Machines, and Long Short-Term Memory (LSTM) neural networks.

Key Features

  • Multi-model sentiment analysis comparison (Logistic Regression, Naive Bayes, Random Forest, SVM, LSTM)
  • Interactive model performance visualizations
  • Detailed model analysis with accuracy, confusion matrix, and classification report
  • Real-time sentiment prediction on user-input text
  • Text preprocessing including HTML tag removal, stopword removal, and tokenization
  • Responsive design for all devices

Technologies Used

PythonStreamlitScikit-learnTensorFlowNLTKPandasNumPyMatplotlibSeaborn

Implementation Details

This application utilizes Scikit-learn for traditional machine learning models and TensorFlow for the LSTM neural network. It implements advanced text preprocessing techniques using NLTK, and leverages Pandas and NumPy for efficient data handling. The interactive visualizations are created using Matplotlib and Seaborn, all integrated seamlessly within a Streamlit interface.

Use Cases

  • Comparative analysis of sentiment analysis models
  • Educational tool for machine learning and NLP concepts
  • Sentiment analysis on custom text inputs
  • Performance benchmarking of different ML/DL approaches

Benefits

  • Provides insights into the strengths and weaknesses of different sentiment analysis models
  • Offers a hands-on learning experience for ML/NLP enthusiasts
  • Enables quick sentiment analysis on custom text
  • Demonstrates the integration of multiple ML libraries in a single application

Project Demo

Pricing

₹400

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