In this project, I developed a Sentiment Analysis Web App using deep learning (CNN) and tradition...

In this project, I developed a Sentiment Analysis Web App using deep learning (CNN) and tradition...In this project, I developed a Sentiment Analysis Web App using deep learning (CNN) and tradition...

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Karan Singh

• Oct 29

In this project, I developed a Sentiment Analysis Web App using deep learning (CNN) and traditional models to classify text sentiment with high accuracy.

The system includes a complete evaluation pipeline comparing CNN, LSTM, Logistic Regression, Random Forest, and Naive Bayes — analyzing performance across multiple iterations and datasets.

Key Highlights:

Built a Streamlit-based web app for real-time sentiment classification

Developed and evaluated multiple models for accuracy and F1-score

Created detailed analysis reports and prototype schematics

Project here → GitHub Repository

Reports: Sentiment Analysis Report (PDF), Product Prototype Diagram

Tech Stack: Python, Streamlit, TensorFlow/Keras, Scikit-learn, Matplotlib