Remove tag production optimization
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Introducing the Pure//Launch Blog

Pure Storage

Introducing the Pure//Launch Blog by Pure Storage Blog The Pure Storage data storage platform is the most innovative in the industry, constantly evolving to meet your data storage needs. Discover how Pure Storage optimizes GenAI apps with RAG. LACP + VLAN tagging support for file virtual interfaces (VIFs): Purity//FA 6.6.4

Capacity 116
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MLOps - Hints and Tips for more Robust Model Deployments

Advancing Analytics

In the previous blog , we explored how Azure Functions can simplify the deployment process. However, there are many other factors to consider when deploying ML models to production environments. In this blog, we'll delve deeper into some of the essential hints and tips for more robust model deployments. This is not robust.

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GIS in Databricks

Advancing Analytics

bz2’ files can have certain tags extracted from them using the ‘options(rowTag=*tag name*)’. The three tags that should be extracted are nodes, ways and relations. alias("id"), f.explode_outer("tag") ).select(f.col("id"), select("id", f.explode_outer("tag")).withColumn("key", select("id", f.explode_outer("tag")).withColumn("key",

Travel 59
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Uncovering Dell EMC’s PowerStore B.S. (Bogus Statements)

Pure Storage

Bogus Statements) by Pure Storage Blog (For the purposes of this post, “B.S.” Item 1: “Built from the ground up”¹ and “Native File Services”² If a system was “built from the ground up,” I’d expect it to look very different from an existing product that was released in April 2019. Uncovering Dell EMC’s PowerStore B.S.

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

Pure Storage

To achieve this, you’ll need to optimize non-sequential (random) read throughput from your storage. Data sets include a mixed bag of “types” of data including millions of small metadata bounding boxes, annotations, tags, etc as well as files and objects of varying sizes. Be able to process all file sizes and formats. The Takeaway.

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

Pure Storage

To achieve this, you’ll need to optimize non-sequential (random) read throughput from your storage. Data sets include a mixed bag of “types” of data including millions of small metadata bounding boxes, annotations, tags, etc as well as files and objects of varying sizes. Be able to process all file sizes and formats. The Takeaway.

Alert 98
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How the SF Giants Use Data Analytics for Partnerships and Marketing

Pure Storage

How the SF Giants Use Data Analytics for Partnerships and Marketing by Pure Storage Blog Like most Major League Baseball (MLB) teams, the San Francisco Giants often experiment with new and innovative ways to bring people to Oracle Park.