INTRODUCTION
How security helps deliver machine
learning results
To build successful machine learning models, you often need datasets unique
to your business. These datasets are extremely valuable assets and need to
be secured throughout every step of the machine learning process—including
data preparation, training, validation, and inference.
In a typical machine learning project, it can take months to build a secure
workflow before you can begin any work on your models. Maintaining
executive buy-in means delivering fast results— so accelerating projects by
weaving security into every step of the process will help ensure organization-
wide commitment to your project and your larger machine learning initiatives.
Amazon SageMaker is a fully managed service that provides every developer
and data scientist with the ability to build, train, and deploy machine learning
models quickly and securely. In this eBook, we provide an overview of the
Amazon SageMaker security features that can help your organization meet
the strict security requirements of machine learning workloads—ultimately
helping you go from idea to production faster, more securely, and with a
higher rate of success.
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