Text Classification focuses on automatically categorizing text data into predefined labels based on its content. It enables organizations to organize large volumes of unstructured text and extract meaningful insights efficiently. This training explains core concepts such as feature extraction, tokenization, and text preprocessing techniques. It also covers machine learning and deep learning models used for classification, including Naive Bayes, logistic regression, and neural networks. You will learn how text classification is applied in spam detection, sentiment analysis, topic labeling, and content filtering. The course also highlights best practices for building accurate, scalable, and production-ready text classification systems.
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