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Answer: TensorFlow Hub, a repository of pre-trained machine learning models ready for fine-tuning and deployment, optimized for GCP., GitHub, as it hosts a wide range of open-source projects and code repositories that can be forked and modified for your needs.
TensorFlow Hub is the most optimal choice because it provides a repository of pre-trained machine learning models that are ready to use, allowing for the reuse of advanced models like R-CNN with minimal coding. These models are specifically optimized for GCP, making it the ideal solution for rapid development. GitHub (A) is a general platform for hosting code and not specifically optimized for ML models on GCP. GCP Marketplace Solutions (B) offers software packages from vendors rather than pre-trained ML models. BigQueryML Open (D) pertains to open data, not pre-trained ML models. Option E is incorrect because only TensorFlow Hub (C) meets the specific requirement of providing pre-trained models optimized for GCP.
Author: LeetQuiz Editorial Team
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Your team is part of an international company utilizing Google Cloud Platform (GCP) for developing, training, and deploying various machine learning (ML) models. The team is currently focused on enhancing efficiency and speed in the workflow. A new project requires the rapid development of an R-CNN model for recognizing photographic images of collaborators and consultants, with the constraint of not starting from scratch to save time and resources. Given the need for a solution that is optimized for GCP and can leverage pre-trained models to accelerate development, which of the following tools would be the most optimal choice? (Choose one correct option)
A
GitHub, as it hosts a wide range of open-source projects and code repositories that can be forked and modified for your needs.
B
GCP Marketplace Solutions, offering a variety of software packages and solutions from third-party vendors that can be deployed on GCP.
C
TensorFlow Hub, a repository of pre-trained machine learning models ready for fine-tuning and deployment, optimized for GCP.
D
BigQueryML Open, providing access to open datasets that can be used for training ML models directly within BigQuery.
E
Both C (TensorFlow Hub) and D (BigQueryML Open) are correct, as they both offer resources that can be utilized for developing the R-CNN model without starting from scratch.