Google Cloud Digital Leader Practice Exam

Google Cloud enhances its machine learning capabilities primarily through TensorFlow, an open-source machine learning framework developed by Google. TensorFlow provides a robust set of tools and libraries that allow developers and organizations to build and train complex machine learning models. It supports various applications, from deep learning to natural language processing, making it versatile for many uses in machine learning.

TensorFlow's scalability and integration with Google Cloud services, such as AI Platform, enable users to deploy their machine learning models in a cloud environment easily. This ecosystem allows for efficient management of resources, computing power, and data storage necessary for training and running ML models. TensorFlow's strong community support and extensive documentation further enhance its appeal as a foundational technology for machine learning tasks, making it the preferred choice in the Google Cloud environment.

Other options, while relevant in their contexts, do not specialize in machine learning to the same level as TensorFlow. GraphQL is primarily a query language for APIs, Hadoop focuses on distributed data processing rather than machine learning, and Node.js is a runtime environment for executing JavaScript on the server side, which does not specifically address machine learning needs.