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5 Hardware Accelerators Every Data Scientist Should Leverage

Smart Data Collective

Although SageMaker has become a popular hardware accelerator since it was launched in 2017, there are plenty of other overlooked hardware accelerators on the market. Companies working on AI technology can use it to improve scalability and optimize the decision-making process. Neptune.ai. Neptune.AI

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AI in Analytics: The NLQ Use Case

Sisense

Once both issues are addressed, the user can ask “how many customers are responsible for 80% of my Q1 2018 income compared to 2017?” and the system will know to look after ‘ clients ’ and aggregate the ‘ revenue ’ (the actual variable names in the system) to compare between Q1 2018 and Q1 2017. Machine Intent vs. User Intent.

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Amazon CloudWatch metrics for Amazon OpenSearch Service storage and shard skew health

AWS Big Data

This solution uses an AWS Lambda function to extract storage and shard distribution metadata from your OpenSearch Service domain, calculates the level of skew, and then pushes this information to CloudWatch metrics so that you can easily monitor, alert, and respond. Gene joined AWS in 2017.

Metrics 93
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Themes and Conferences per Pacoid, Episode 11

Domino Data Lab

In other words, using metadata about data science work to generate code. SQL optimization provides helpful analogies, given how SQL queries get translated into query graphs internally , then the real smarts of a SQL engine work over that graph. A Program Synthesis Primer ” – Aws Albarghouthi (2017-04-24).

Metadata 105
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What are model governance and model operations?

O'Reilly on Data

In a previous post , we noted some key attributes that distinguish a machine learning project: Unlike traditional software where the goal is to meet a functional specification, in ML the goal is to optimize a metric. Metadata and artifacts needed for a full audit trail.

Modeling 194
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If Johnny Mnemonic Smuggled Linked Data

Ontotext

It’s the dawn of a yet another Forrester report ( TechRadar : Artificial Intelligence Technologies, Q1 2017 ) highlighting the importance and the potential of semantic technology to represent and govern knowledge. TechRadar: Artificial Intelligence Technologies, Q1 2017. Linked Data and Information Retrieval.

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Real-Real-World Programming with ChatGPT

O'Reilly on Data

To provide some coherence to the music, I decided to use Taylor Swift songs since her discography covers the time span of most papers that I typically read: Her main albums were released in 2006, 2008, 2010, 2012, 2014, 2017, 2019, 2020, and 2022. This choice also inspired me to call my project Swift Papers.