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Text Classification in Python Guide by rahacse is a document available to read on EtoBox.

What is Text Classification in Python Guide about?

This document provides a comprehensive guide to understanding and implementing text classification in Python. It discusses the key steps in a text classification pipeline, including dataset preparation, feature engineering, and model training. For feature engineering, it covers techniques like count vectors, TF-IDF vectors at the word, n-gram, and character level, word embeddings, and text-based features. The goal is to transform raw text into feature vectors that can be used to train machine learning model

Author

rahacse

Language

EN