Skip to content
#

review-analyzer

Here are 6 public repositories matching this topic...

Language: All
Filter by language

Advanced AI-powered customer feedback analysis platform with custom-trained BERT models achieving 95.1% sentiment accuracy. Features real-time processing, RTX 4060 GPU acceleration, business intelligence dashboard, bulk CSV/PDF analysis with Gemini API, and Google Material Design 3.0 interface. Enterprise-grade solution for consumer feedback

  • Updated Oct 25, 2025
  • Python

A neural network model for sentiment analysis of movie reviews using IMDb dataset. The model is built using PyTorch and BERT as the feature extractor.

  • Updated Feb 10, 2023
  • Jupyter Notebook

Turn WooCommerce reviews into clear, actionable insights without manual reading. This n8n workflow automation analyzes customer reviews using GPT-4, stores structured feedback in Airtable and sends concise sentiment summaries to Slack — helping teams spot issues, trends and wins faster with a flexible n8n workflow template.

  • Updated Jan 3, 2026

📊 Analyze customer reviews with AI-driven sentiment insights to enhance strategies and improve brand perception. Ideal for marketing and operations teams.

  • Updated Jan 4, 2026
  • Python

Improve this page

Add a description, image, and links to the review-analyzer topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the review-analyzer topic, visit your repo's landing page and select "manage topics."

Learn more