Text Classification Models - Deep Learning Approaches: Studying deep learning approaches for text classification tasks such as sentiment analysis, topic classification, and document categorization

Abstract

Text classification is a fundamental task in natural language processing (NLP) with applications ranging from sentiment analysis to document categorization. Deep learning approaches have shown remarkable performance in various text classification tasks, leveraging neural network architectures to learn complex patterns from text data. This paper provides a comprehensive review of deep learning models for text classification, focusing on their applications, architectures, training strategies, and performance benchmarks. We discuss key challenges and future research directions in the field, aiming to provide insights for researchers and practitioners working in NLP and related areas.