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Copyright, AI, and Provenance

O'Reilly on Data

I can also ask for a reading list about plagues in 16th century England, algorithms for testing prime numbers, or anything else. Yes, it happens to be the next word in Hamlet’s famous soliloquy; but the model wasn’t copying Hamlet, it just picked “or” out of the hundreds of thousands of words it could have chosen, on the basis of statistics.

Modeling 253
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6 DataOps Best Practices to Increase Your Data Analytics Output AND Your Data Quality

Octopai

Continuous pipeline monitoring with SPC (statistical process control). SPC is the continuous testing of the results of automated manufacturing processes. products or product components) are checked to make sure that they do not deviate in a statistically significant way from the expected results. Results (i.e.

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Amazon DataZone now integrates with AWS Glue Data Quality and external data quality solutions

AWS Big Data

Visualize AWS Glue Data Quality scores in Amazon DataZone You can now visualize AWS Glue Data Quality scores in data assets that have been published in the Amazon DataZone business catalog and that are searchable through the Amazon DataZone web portal. We use this data source to import metadata information related to our datasets.

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Bringing the National Museum of African American History and Culture to the world

CIO Business Intelligence

Digital storytelling To entice a technical partner to build the digital site, the ODSE published an RFP and received 15 qualified IT specialists that wanted to take on the immense task of digitally recreating a multifloor museum.

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The AIgent: Using Google’s BERT Language Model to Connect Writers & Representation

Insight

There was only one problem: literary agents, the gatekeepers of the publishing industry, kept rejecting the book?—?often Galbraith eventually opted to publish Cuckoo’s Calling through an acquaintance of sorts. but the publishing industry failed to see it. Data Collection The AIgent leverages book synopses and book metadata.

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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

It involves: Reviewing data in detail Comparing and contrasting the data to its own metadata Running statistical models Data quality reports. Also known as data validation, integrity refers to the structural testing of data to ensure that the data complies with procedures. 2 – Data profiling. date, month, and year).

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What you need to know about product management for AI

O'Reilly on Data

All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. This has serious implications for software testing, versioning, deployment, and other core development processes. Machine learning adds uncertainty.