Auto-Tagging System for Content Categorization

In this project, we’ll get hands-on practice in Python and natural language processing (NLP). We’ll use spaCy, an advanced NLP library in Python, to tackle the challenge of automating content tagging. Our goal is to develop an automated system capable of efficiently tagging textual content. We’ll gain practical experience in text preprocessing, familiarity with spaCy’s robust features, and building a model pipeline that can predict tags accurately.

We’ll primarily utilize spaCy for text preprocessing, entity recognition, and tag generation due to its robust NLP capabilities. For specific text-cleaning tasks, we’ll also take the help of the re library for regular expressions (regex). Additionally, we fine-tune spaCy’s pretrained models with our custom dataset and evaluate the model’s performance using test data, ensuring our tags are accurate and relevant to the content.