Text Classification
Text classification is a natural language processing (NLP) task that involves categorizing text documents or snippets into predefined classes or labels based on their content. It is a supervised learning problem where a model is trained on labeled data to predict the category of new, unseen text. Common applications include spam detection, sentiment analysis, topic labeling, and intent recognition.
Developers should learn text classification to build intelligent systems that can automatically organize, filter, and analyze large volumes of textual data, such as emails, social media posts, or customer reviews. It is essential for applications like content moderation, recommendation systems, and automated customer support, where efficiency and scalability are critical.