Text Classification Using PyTorch

Text classification is a fundamental task in natural language processing (NLP) that aims to categorize text documents into predefined classes or categories automatically. It has numerous real-world applications, such as sentiment analysis, spam detection, topic classification, customer feedback analysis, and currently, classifying text as generated by an AI model or not.

In this project, we’ll practice preprocessing text data, extracting meaningful features, and training machine learning models to perform classification. Specifically, we’ll build a question classifier. The project emphasizes the use of neural networks, including pre-trained language models, while also providing an introduction to traditional machine learning techniques. We’ll use popular Python NLP libraries and frameworks like NLTK, scikit-learn, and PyTorch.