Which of the following are included as AI training and inference frameworks?

The selection of MindSpore, PyTorch, and TensorFlow as AI training and inference frameworks is accurate because these three are specifically designed to support the development, training, and deployment of machine learning and deep learning models.

MindSpore is Huawei's own deep learning framework that provides a comprehensive environment for developing AI applications. It emphasizes ease of use, scalability, and efficient computation, especially suited for diverse AI scenarios. PyTorch is an open-source machine learning library known for its flexibility and dynamic computation graph, making it particularly popular among researchers. TensorFlow is another widely adopted open-source framework that supports various functionalities, including distributed computing, making it suitable for both research and production environments.

Other options such as Pandas and Scikit-learn serve important roles in data handling and analysis, as well as facilitating machine learning processes, but they are not primarily classified as training and inference frameworks. Pandas is mainly used for data manipulation and analysis, while Scikit-learn provides simple and efficient tools for data mining and data analysis, focused predominantly on classical machine learning algorithms rather than deep learning frameworks. Matplotlib is a plotting library and does not relate to model training or inference directly.