Remove tag data-science
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What's in a name? Naming your Fabric artifacts

Advancing Analytics

Engineering Practices But if I put my Data Engineer hat on, I’ve always been a fan of a robust naming convention. And taking that a step further, most data teams I’ve worked in have also been keen to adopt similar patterns for Data Factory and Synapse Analytics components too. So is a solid naming convention a good idea?

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Intelligent Alert Grouping Series Summary by Quintessence Anx

PagerDuty

Co-authored by Chris Bonnell, PagerDuty Data Scientist VI. I hope you’ve enjoyed this series, and if you’d like to take a look at any of our prior posts, please use the ei-architecture-series tag. If you’d like to reference these posts in the longer term, please bookmark the ei-architecture-series tag. Key Takeaways.

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MLOps - Hints and Tips for more Robust Model Deployments

Advancing Analytics

We'll look at topics such as proper model versioning and packaging, data validation, and performative code optimisations. By implementing these practices, data scientists and ML engineers can ensure their models are deployed efficiently, accurately, and with minimal downtime.

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Happy Birthday, Instagram: Social Media Giant Turns 12

Pure Storage

It’s also one of the most massive sources of unstructured data out there—with users posting new photos and videos every second. Let’s look at its evolution and how data and technology have played a role. . He also wanted users to have the ability to tag both people and locations in photos. .

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AI Developers: 6 Reasons You Should Care about Better Data Storage

Pure Storage

An effective AI process simplifies the work of developers and data scientists and minimizes all bottlenecks within the flow of data from sources to accurate outcomes. Do you find yourself wishing that data sets loaded and copied faster? Before training starts, it’s important to examine the contents of the data set.

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3 Ways Telecoms Can Future-proof Communications

Pure Storage

In the past decade alone, over-the-top (OTT) services like WhatsApp have forced telecoms to completely change their business model priorities, shifting the value of their consumer plans from calls and SMS to data. But not all telecoms are meeting these demands head-on or realizing how fundamental data is to their success.

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AI Developers: 7 Reasons You Should Care about Better Data Storage

Pure Storage

An effective AI process simplifies the work of developers and data scientists and minimizes all bottlenecks within the flow of data from sources to accurate outcomes. Do you find yourself wishing that data sets loaded and copied faster? Before training starts, it’s important to examine the contents of the data set.

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