PyTorch Forum Analysis Project

A comprehensive data science project analyzing 73,000+ PyTorch Forum topics using state-of-the-art NLP techniques including semantic embeddings, unsupervised clustering, and interactive visualization.

This project demonstrates advanced machine learning techniques applied to real-world forum data, showcasing the power of semantic understanding and cluster analysis for large-scale text collections.

Access the Analysis

📊 Complete Analysis Report 2D Clustering Visualization 3D Clustering Visualization

Technical Highlights

  • Data Processing: Analyzed 73,000+ forum topics with comprehensive metadata
  • Embeddings: Semantic embeddings using all-MiniLM-L12-v2 model
  • Clustering: K-Means and HDBSCAN with silhouette score optimization
  • Visualization: Interactive 2D/3D plots with UMAP and t-SNE dimensionality reduction
  • Analysis: Word clouds, TF-IDF keywords, and temporal trend analysis
  • Evaluation: Comprehensive metrics including ARI, NMI, V-Measure, and silhouette scores

The complete analysis showcases an end-to-end data science pipeline with detailed methodology, results, and reproducible code.