TEXT ANALYSIS TECHNIQUES USING MACHINE LEARNING ALGORITHMS
Abstract
Text analysis, a crucial area within natural language processing (NLP), employs machine learning algorithms to extract meaningful insights from textual data. This thesis explores the primary techniques used in text analysis, detailing the processes involved in data collection, preprocessing, model training, and evaluation. Emphasis is placed on the practical applications and comparative effectiveness of different machine learning algorithms. A comparison table summarizing the key characteristics of these algorithms is included to facilitate understanding.
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