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Google Cloud Certified Cloud Digital Leader · Google Cloud
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The correct answer is A. TensorFlow because it is an open-source machine learning platform that allows organizations to build and deploy custom machine learning models, including support for Google Cloud TPUs (Tensor Processing Units) to accelerate training and inference. Why Not the Other Options? B. BigQuery ML – Used for training ML models using SQL queries, but it does not provide full flexibility for building custom ML applications or TPU support. C. Vision API – A pre-trained API for image analysis, not for custom ML model development. D. AutoML Vision – A no-code/low-code solution for image classification, but it does not provide the full customization or TPU support needed for complex ML applications.
A. Is correct TensorFlow is an open-source machine learning framework developed by Google. It is highly compatible with TPUs (Tensor Processing Units), which are specialized hardware accelerators designed to speed up machine learning workloads12. TensorFlow provides extensive support for training and deploying machine learning models on TPUs, making it an ideal choice for leveraging the high performance and scalability of TPUs3. Options B, C, and D are not open-source platforms and are more specialized services that do not offer the same level of flexibility and integration with TPUs as TensorFlow.
Correct Answer is- A. TensorFlow. Explanation: TensorFlow is an open-source machine learning framework developed by Google that is specifically designed to leverage TPUs (Tensor Processing Units) effectively. It provides comprehensive support for building, training, and deploying machine learning models, including those that can take advantage of TPU architecture for accelerated performance. TensorFlow's integration with TPUs allows developers to optimize their machine learning workloads, making it the ideal choice for organizations looking to utilize TPUs in their applications.