Google Cloud AI Platform is a managed service that enables developers and data scientists to build, deploy, and manage machine learning models at scale. It provides tools for training, tuning, and serving models in a production environment, facilitating end-to-end machine learning workflows.
About Google Cloud AI Platform
Google Cloud AI Platform was launched by Google in 2018 to provide an integrated environment for building, deploying, and managing machine learning models. It aimed to streamline the machine learning workflow, making it easier for developers and data scientists to leverage Google's infrastructure and tools for scalable model training and deployment.
Strengths of Google Cloud AI Platform include robust scalability, integration with other Google Cloud services, and advanced machine learning tools. Weaknesses include potential complexity for beginners and higher costs compared to some alternatives. Competitors include AWS SageMaker, Microsoft Azure Machine Learning, and IBM Watson.
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How to hire a Google Cloud AI Platform expert
A Google Cloud AI Platform expert must have skills in machine learning model development, proficiency in TensorFlow, familiarity with cloud computing concepts, experience with Google Cloud services such as BigQuery and Cloud Storage, and knowledge of Python programming.
*Estimations are based on information from Glassdoor, salary.com and live Howdy data.
USA
$ 224K
Employer Cost
$ 127K
Employer Cost
$ 97K
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