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Using PyTorch in the Cloud

PyTorch Playbook

Janani Ravi

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Deep Learning Cloud Computing Distributed Training PyTorch GCP Machine Learning AWS

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Teaches how to deploy PyTorch models in cloud environments, including AWS, Azure, and GCP

Suitable for learners with a basic understanding of PyTorch and cloud computing

Instructors are experienced practitioners in the field of PyTorch and cloud computing

Requires learners to have access to cloud computing resources, which may incur costs

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Career center

Learners who complete Using PyTorch in the Cloud: PyTorch Playbook will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

The Machine Learning Engineer is responsible for designing, developing, deploying, and maintaining machine learning models. This course can help you become a Machine Learning Engineer by providing you with the skills and knowledge to use PyTorch, a popular deep learning framework, on each of the big three cloud providers: Amazon Web Services (AWS), Microsoft Azure, and the Google Cloud Platform (GCP).

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Data Scientist

The Data Scientist is responsible for collecting, analyzing, and interpreting data to help businesses make better decisions. This course can help you become a Data Scientist by providing you with the skills and knowledge to use PyTorch to build deep learning models that can be used to analyze data and make predictions.

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Deep Learning Engineer

The Deep Learning Engineer is responsible for designing, developing, and deploying deep learning models. This course can help you become a Deep Learning Engineer by providing you with the skills and knowledge to use PyTorch, a popular deep learning framework, on each of the big three cloud providers: Amazon Web Services (AWS), Microsoft Azure, and the Google Cloud Platform (GCP).

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Cloud Architect

The Cloud Architect is responsible for designing and implementing cloud-based solutions. This course can help you become a Cloud Architect by providing you with the skills and knowledge to use PyTorch on each of the big three cloud providers: Amazon Web Services (AWS), Microsoft Azure, and the Google Cloud Platform (GCP).

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Software Engineer

The Software Engineer is responsible for designing, developing, and maintaining software applications. This course can help you become a Software Engineer by providing you with the skills and knowledge to use PyTorch, a popular deep learning framework, on each of the big three cloud providers: Amazon Web Services (AWS), Microsoft Azure, and the Google Cloud Platform (GCP).

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Data Analyst

The Data Analyst is responsible for collecting, analyzing, and interpreting data to help businesses make better decisions. This course may be useful for you if you want to become a Data Analyst, as it will provide you with the skills and knowledge to use PyTorch to build deep learning models that can be used to analyze data and make predictions.

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Business Intelligence Analyst

The Business Intelligence Analyst is responsible for collecting, analyzing, and interpreting data to help businesses make better decisions. This course may be useful for you if you want to become a Business Intelligence Analyst, as it will provide you with the skills and knowledge to use PyTorch to build deep learning models that can be used to analyze data and make predictions.

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Quantitative Analyst

The Quantitative Analyst is responsible for using mathematical and statistical models to analyze data and make predictions. This course may be useful for you if you want to become a Quantitative Analyst, as it will provide you with the skills and knowledge to use PyTorch to build deep learning models that can be used to analyze data and make predictions.

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Financial Analyst

The Financial Analyst is responsible for analyzing financial data to help businesses make better decisions. This course may be useful for you if you want to become a Financial Analyst, as it will provide you with the skills and knowledge to use PyTorch to build deep learning models that can be used to analyze financial data and make predictions.

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Investment Analyst

The Investment Analyst is responsible for analyzing investment data to help businesses make better decisions. This course may be useful for you if you want to become an Investment Analyst, as it will provide you with the skills and knowledge to use PyTorch to build deep learning models that can be used to analyze investment data and make predictions.

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Risk Analyst

The Risk Analyst is responsible for identifying and assessing risks to help businesses make better decisions. This course may be useful for you if you want to become a Risk Analyst, as it will provide you with the skills and knowledge to use PyTorch to build deep learning models that can be used to identify and assess risks.

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Operations Research Analyst

The Operations Research Analyst is responsible for using mathematical and statistical models to help businesses make better decisions. This course may be useful for you if you want to become an Operations Research Analyst, as it will provide you with the skills and knowledge to use PyTorch to build deep learning models that can be used to make better decisions.

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Management Consultant

The Management Consultant is responsible for helping businesses improve their performance. This course may be useful for you if you want to become a Management Consultant, as it will provide you with the skills and knowledge to use PyTorch to build deep learning models that can be used to analyze data and make recommendations for improvement.

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Product Manager

The Product Manager is responsible for developing and managing products. This course may be useful for you if you want to become a Product Manager, as it will provide you with the skills and knowledge to use PyTorch to build deep learning models that can be used to analyze data and make decisions about product development.

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Marketing Manager

The Marketing Manager is responsible for developing and implementing marketing campaigns. This course may be useful for you if you want to become a Marketing Manager, as it will provide you with the skills and knowledge to use PyTorch to build deep learning models that can be used to analyze data and make decisions about marketing campaigns.

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