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Google Professional Machine Learning Engineer

Google Professional Machine Learning Engineer

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You are managing a team of data scientists who are currently using a cloud-based backend system to submit their machine learning training jobs. Due to the increasing complexity and difficulty in administering this system, you are considering transitioning to a managed service. The team uses multiple frameworks for their work, including Keras, PyTorch, Theano, scikit-learn, and custom libraries. You need a solution that supports these diverse frameworks and simplifies the job submission process. What should you do?

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