AWS Machine Learning Blog

FEBRUARY 7, 2024

In the first post of this three-part series, we presented a solution that demonstrates how you can automate detecting document tampering and fraud at scale using AWS AI and machine learning (ML) services for a mortgage underwriting use case. Data must reside in Amazon S3 in an AWS Region supported by the service.

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The MLOps Blog

JUNE 27, 2023

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. and Pandas or Apache Spark DataFrames.

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Machine Learning Machine Learning ML ML 134

Heartbeat

JUNE 12, 2023

Many tools and techniques are available for ML model monitoring in production, such as automated monitoring systems, dashboarding and visualization, and alerts and notifications. Organizations can ensure that their machine-learning models remain robust and trustworthy over time by implementing effective model monitoring practices.

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Machine Learning Machine Learning ML ML 98

AWS Machine Learning Blog

APRIL 18, 2023

To improve this experience for its members, we at RallyPoint wanted to explore how machine learning (ML) could help. The sample set of de-identified, already publicly shared data included thousands of anonymized user profiles, with more than fifty user-metadata points, but many had inconsistent or missing meta-data/profile information.

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DagsHub

AUGUST 23, 2024

As companies increasingly rely on data for decision-making, poor-quality data can lead to disastrous outcomes. Even the most sophisticated ML models, neural networks, or large language models require high-quality data to learn meaningful patterns. When bad data is inputted, it inevitably leads to poor outcomes.

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Data Quality Data Governance Machine Learning Machine Learning 52