Remove 2017 Remove Metadata Remove Modeling
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What are model governance and model operations?

O'Reilly on Data

A look at the landscape of tools for building and deploying robust, production-ready machine learning models. We are also beginning to see researchers share sample code written in popular open source libraries, and some even share pre-trained models. Model development. Model governance. Source: Ben Lorica.

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Cloudera Enables Hybrid Cloud Data and AI

David Menninger's Analyst Perspectives

Cloudera made its debut on the New York Stock Exchange in 2017 before merging with fellow Hadoop provider Hortonworks in 2019 amid market consolidation and a shift toward object storage as the persistence layer for data processing both on-premises and in the cloud.

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Themes and Conferences per Pacoid, Episode 11

Domino Data Lab

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. In other words, using metadata about data science work to generate code. Using ML models to search more effectively brought the search space down to 102—which can run on modest hardware. Introduction. That’s impressive.

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Gartner Magic Quadrant for Metadata Management Includes Alation

Alation

Gartner predicts that “By 2020, 50% of information governance initiatives will be enacted with policies based on metadata alone.”. Magic Quadrant for Metadata Management Solutions , Guido de Simoni and Roxane Edjlali, August 10, 2017. Metadata management no longer refers to a static technical repository.

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What Are ChatGPT and Its Friends?

O'Reilly on Data

It’s important to understand that ChatGPT is not actually a language model. It’s a convenient user interface built around one specific language model, GPT-3.5, is one of a class of language models that are sometimes called “large language models” (LLMs)—though that term isn’t very helpful. with specialized training.

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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. This feature helps automate many parts of the data preparation and data model development process. A data visualization interface known as SPSS Modeler. Neptune.ai.

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AI in Analytics: The NLQ Use Case

Sisense

NLQ serves those users who are in a rush, or who lack the skills or permissions to model their data using visualization tools or code editors. Last, and still a very painful challenge for most users, is the familiarity with the underlying data and data model. when the user actually meant to compare between Q1 2018 to the whole of 2017?