What does Python use for Natural Language Processing?1 pointNatural Language ToolkitKerasTensorFlowPandas

Breaking Down the Problem

1. Identify the tools or libraries used for Natural Language Processing (NLP) in Python.
2. Evaluate each option to see if it is commonly used for NLP.

Relevant Concepts

• Natural Language Processing is a field that involves techniques and tools designed to process and analyze human language.
• Libraries in Python can be specialized for machine learning, data manipulation, and specific tasks in NLP.

Analysis and Detail

1. Natural Language Toolkit (NLTK): A leading platform for building Python programs to work with human language data. It's widely used for NLP tasks such as classification, tokenization, stemming, tagging, parsing, and semantic reasoning.
2. Keras: A high-level neural networks API, Keras is primarily used for deep learning and can be applied to NLP tasks but is not dedicated exclusively to NLP.
3. TensorFlow: An open-source platform for machine learning that can support NLP tasks through its libraries. However, it requires more implementation effort compared to dedicated NLP libraries.
4. Pandas: Primarily a data manipulation and analysis library. While it can be utilized in data preprocessing for NLP, it is not specifically designed for handling text data or NLP tasks.

Verify and Summarize

Among the options listed, the most recognized and specifically designed library for Natural Language Processing in Python is the Natural Language Toolkit (NLTK). Keras and TensorFlow can also be used for NLP, but they are more generalized machine learning frameworks. Pandas, while very useful for handling data, is not an NLP library.

Final Answer

The correct answer is Natural Language Toolkit (NLTK).