
Text Preprocessing
Text preprocessing is the process of cleaning and transforming raw text data into a format that can be easily analyzed and understood by machine learning algorithms. This involves several steps such as removing punctuation, converting all text to lowercase, removing stop words, stemming or lemmatizing words, and converting text into numerical representations such as vectors or matrices. Text preprocessing is an important step in natural language processing (NLP) and is essential for tasks such as sentiment analysis, topic modeling, and text classification. It helps to improve the accuracy and efficiency of machine learning models by reducing noise and irrelevant information in the text data.
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