Answer: Removes noise and reduces input size

This process is called **stop word removal** in natural language processing (NLP). The main benefits are: - **Removes noise**: Common words like "the," "is," and "and" don't typically carry meaningful information for classification tasks - **Reduces input size**: By eliminating these frequent but uninformative words, the dataset becomes smaller and more manageable - **Improves model efficiency**: With fewer tokens to process, training and inference become faster - **Focuses on meaningful content**: The model can concentrate on words that actually contribute to classification decisions This preprocessing step is particularly important for text classification models to improve performance and reduce computational requirements.

Author: Ritesh Yadav