Text Classification
Text classification is the process of categorizing text data into predefined categories based on its content. It is a supervised learning technique in machine learning and natural language processing that involves training a model on a labeled dataset to predict the category of new, unseen text data. Text classification has various applications such as spam filtering, sentiment analysis, topic modeling, and language identification. The process involves several steps including data preprocessing, feature extraction, model training, and evaluation. Commonly used algorithms for text classification include Naive Bayes, Support Vector Machines, and Neural Networks.
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