Which library is known as a free, open-source machine learning library for Python that supports a wide range of algorithms and tools?

Scikit-learn is recognized as a free, open-source machine learning library for Python that provides a comprehensive array of algorithms and tools designed specifically for data mining and data analysis. Its strong emphasis on simplicity and ease of use, alongside efficient implementations of various supervised and unsupervised learning algorithms, makes it a popular choice among data scientists and machine learning practitioners. Scikit-learn supports tasks such as classification, regression, clustering, dimensionality reduction, model selection, and preprocessing of data, making it extremely versatile for a wide range of applications.

In the context of the other options, TensorFlow, while also open-source and a powerful library for machine learning, is particularly geared towards deep learning and neural network architectures rather than providing a broader toolbox for generally accessible machine learning tasks. Pandas primarily focuses on data manipulation and analysis, offering data structures and functions for efficiently handling structured data but does not specifically cater to machine learning models. Keras is primarily a high-level neural networks API that runs on top of TensorFlow, allowing for easier implementation of deep learning models but does not encompass the broader range of machine learning algorithms provided by Scikit-learn. Thus, Scikit-learn is the most fitting choice for its comprehensive approach to machine learning.