Website Categorization Using an RNN

This project implements a Recurrent Neural Network (RNN) to classify websites into predefined categories based on their content. The primary workflow involves fetching the title of a webpage from its URL, processing it, and predicting its category using a pre-trained model.

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Features

1. RNN-based Classification

• Utilizes an RNN with pre-trained embeddings for efficient and accurate text categorization.

2. HTML Parsing

• Automatically fetches and processes webpage titles using the BeautifulSoup library.

3. Imbalanced Dataset Handling

• Balances training data for top categories to improve model generalization.

4. Pre-trained Embeddings

• Leverages GloVe embeddings for enhanced word representation.

5. Transfer Learning

• Fine-tuned for better performance on the provided dataset.

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For a detailed walkthrough, check out the full article on Medium:
Website Classifier using RNN