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Monitoring Machine Learning Models in Production

Heartbeat

Source: Author Introduction Machine learning model monitoring tracks the performance and behavior of a machine learning model over time. Organizations can ensure that their machine-learning models remain robust and trustworthy over time by implementing effective model monitoring practices.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

How to evaluate MLOps tools and platforms Like every software solution, evaluating MLOps (Machine Learning Operations) tools and platforms can be a complex task as it requires consideration of varying factors. An integrated model factory to develop, deploy, and monitor models in one place using your preferred tools and languages.

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Automate mortgage document fraud detection using an ML model and business-defined rules with Amazon Fraud Detector: Part 3

AWS Machine Learning Blog

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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How and When to Use Dataflows in Power BI

phData

Attach a Common Data Model Folder (preview) When you create a Dataflow from a CDM folder, you can establish a connection to a table authored in the Common Data Model (CDM) format by another application. We suggest prioritizing efficiency in your model designs by ensuring query folding whenever it is feasible.

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Capital One’s data-centric solutions to banking business challenges

Snorkel AI

Three experts from Capital One ’s data science team spoke as a panel at our Future of Data-Centric AI conference in 2022. Please welcome to the stage, Senior Director of Applied ML and Research, Bayan Bruss; Director of Data Science, Erin Babinski; and Head of Data and Machine Learning, Kishore Mosaliganti.

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Capital One’s data-centric solutions to banking business challenges

Snorkel AI

Three experts from Capital One ’s data science team spoke as a panel at our Future of Data-Centric AI conference in 2022. Please welcome to the stage, Senior Director of Applied ML and Research, Bayan Bruss; Director of Data Science, Erin Babinski; and Head of Data and Machine Learning, Kishore Mosaliganti.

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Comparing Tools For Data Processing Pipelines

The MLOps Blog

If you will ask data professionals about what is the most challenging part of their day to day work, you will likely discover their concerns around managing different aspects of data before they get to graduate to the data modeling stage. How frequently you would require to transfer the data is also of key interest.