Using NLP for Text-based Product Classification

Natural Language Processing (NLP) excels in analyzing textual data like product descriptions. Techniques include:

Text Tokenization: Splitting text into meaningful words or phrases.
Vectorization: Representing text as numerical data using methods like TF-IDF or word embeddings (e.g., Word2Vec, BERT).
Text Classification Models: Algorithms like Naive Bayes or deep learning models like Transformers can categorize textual data.
For example, the title "Red Cotton Shirt for Men" can be tokenized and vectorized to classify it under "Clothing > Men's Shirts."