Machine learning (ML) can be a complex process for any size company. The lack of integration between workflow steps and tools not only makes it difficult, but time-consuming. That’s why startups use Amazon SageMaker to build, train, and deploy ML models. We'll dive deep into demonstrating SageMaker’s advanced features that help you train and iterate on your ML models faster. You'll learn techniques to transform your ML research project into a production-ready service.
Discover how to set up a data lake and implement it into an ML experiment workflow, how to prepare an end-t...
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