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. Save model: This step creates a model from the trained model artifacts.

Management 110

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AWS Machine Learning

APRIL 13, 2023

Accenture is using Amazon CodeWhisperer to accelerate coding as part of our software engineering best practices initiative in our Velocity platform,” says Balakrishnan Viswanathan, Senior Manager, Tech Architecture at Accenture. Ankur Desai is a Principal Product Manager within the AWS AI Services team.

Scripts 84

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AWS Machine Learning

FEBRUARY 13, 2023

According to Accenture , companies that manage to efficiently scale AI and ML can achieve nearly triple the return on their investments. An administrator can run the AWS CDK script provided in the GitHub repo via the AWS Management Console or in the terminal after loading the code in their environment.

Scripts 74

Scripts Best practices Transportation Construction 74

AWS Machine Learning

NOVEMBER 1, 2022

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. However, a lot of these processes are still currently done manually by a data engineer or analyst who analyzes the data using these tools. Prerequisites.

Engineering 91

Engineering APIs Accountability industry solution 91

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. You can also add your own Python scripts and transformations to customize workflows.

Best practices 78

Best practices Scripts Education Engineering 78