Machine learning libraries are powered by artificial intelligence (AI) technologies, which utilize algorithms to analyze and interpret data. Frameworks such as TensorFlow, PyTorch, and Scikit-learn enable developers to build, train, and deploy machine learning models efficiently. These libraries provide pre-built functions for tasks like data preprocessing, model evaluation, and algorithm selection, streamlining the machine learning workflow. By abstracting complex mathematical operations, these libraries make machine learning more accessible, allowing researchers and practitioners to focus on innovative applications rather than the underlying technicalities.