Pure Storage

OCTOBER 24, 2022

Training models are the clearest interaction between developers and storage. GPUs process data quickly, so you want your data to be accessible from storage that performs well and scales predictably. During a training job, most scripts write out a checkpoint of the model file back to storage. The Takeaway.

Alert 124

Alert Security Resilience Management 124

Pure Storage

OCTOBER 19, 2022

Training models are the clearest interaction between developers and storage. GPUs process data quickly, so you want your data to be accessible from storage that performs well and scales predictably. During a training job, most scripts write out a checkpoint of the model file back to storage. The Takeaway.

Alert 98

Alert Security Resilience Management 98

Pure Storage

SEPTEMBER 11, 2023

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.

Marketing 64

Marketing Sports Media Advertising 64

Pure Storage

NOVEMBER 1, 2022

As ML applications receive new data, they learn, adapt, and improve their accuracy to make more accurate predictions and provide greater insights. . Data scientists train machine learning algorithms using large amounts of data, which allows them to identify patterns and make predictions when they encounter new situations.

Application 59

Application Automotive Capacity Technology 59

Pure Storage

JULY 21, 2023

Data Fabric vs. Data Lake vs. Data Warehouse by Pure Storage Blog As businesses collect more “raw” data—such as computer logs or video files that have not yet been processed, cleaned, or analyzed for use—they need reliable and effective ways to manage that information until they’re ready to work with it.

Architecture 52

Architecture Data Integrity Application Government 52