AWS Machine Learning
JANUARY 5, 2024
Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models. Data science and DevOps teams may face challenges managing these isolated tool stacks and systems. Based on the output, the next step is to create or update the endpoint.
TechSee
MARCH 7, 2023
Taksina Eammano, EVP & GM Field Service, Salesforce – Taksina is leading the conversation in applying AI and workflow to manage cost and improve field service outcomes while improving customer experience in the SFDC Field Service Customers. Kate champions digital innovations that create the best customer experience and solutions.
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AWS Machine Learning
DECEMBER 19, 2023
Data and model management provide a central capability that governs ML artifacts throughout their lifecycle. Amazon SageMaker Role Manager is used to implement role-based ML activity, and Amazon S3 is used to store input data and artifacts. AWS CDK provides the ability to manage changes for the complete solution.
AWS Machine Learning
SEPTEMBER 23, 2022
Bosch is a multinational corporation with entities operating in multiple sectors, including automotive, industrial solutions, and consumer goods. These metrics provide business planning insights at different levels of aggregation and enable data-driven decision-making. Evaluation metrics. Modeling approaches. Evaluation.
AWS Machine Learning
APRIL 25, 2023
Amazon SageMaker Model Training helps data scientists run fully managed large-scale training jobs on AWS’s compute infrastructure. You have the flexibility to customize your runtime in the SageMaker managed infrastructure using the inferred configuration or override them at the SDK-level by passing them as arguments to the decorator.
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