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AWS Machine Learning
FEBRUARY 6, 2024
This solution uses the SageMaker JumpStart AI21 Jurassic Jumbo Instruct and AI21 Summarize models to extract and create the documents. The following diagram illustrates the solution architecture. The workflow consists of the following steps: A user accesses the regulatory document authoring tool from their computer browser.
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. SageMaker comes with the necessary tools for scaling a model during inference.
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AWS Machine Learning
NOVEMBER 1, 2022
The tools and technologies to assist with data preprocessing have been growing over the years. Now we have low-code and no-code tools like Amazon SageMaker Data Wrangler , AWS Glue DataBrew , and Amazon SageMaker Canvas to assist with data feature engineering. The following figure illustrates our Step Function workflow.
AWS Machine Learning
FEBRUARY 13, 2023
With the advancements in automation and configuring with increasing levels of abstraction to set up different environments with IaC tools, the AWS CDK is being widely adopted across various enterprises. He works with AABG to develop and implement innovative cloud solutions, and specializes in infrastructure as code and cloud security.
Cincom
MAY 8, 2024
CPQ solutions enhance sales effectiveness by simplifying quoting, centralizing product data, recommending optimal deals, and automating repetitive administrative workflows. Core CPQ features include: Guided Selling Tools: CPQ applies configuration requirements and logic when building customized quotes.
AWS Machine Learning
JUNE 14, 2023
Amazon SageMaker is a fully managed service to prepare data and build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows. We demonstrate how to use CI/CD the low-code/no-code tools code to integrate it into your MLOps environment, while adhering with MLOps best practices.
AWS Machine Learning
OCTOBER 21, 2024
This feature empowers customers to import and use their customized models alongside existing foundation models (FMs) through a single, unified API. This unified experience enables developers to use the same tooling and workflows across both base FMs and imported custom models. Be backed by enterprise grade security and privacy tooling.
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