AutoML and Declarative Machine Learning: Comparing Use Cases
ABSTRACT :
AutoML and the emerging approach of declarative ML help simplify the process of creating and refining ML models.
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Register now for - "Analytics for Power Users: Practices and Products You Need to Know" - Wednesday, December 13, 11:30 a.m. Eastern Time.
ABSTRACT :
AutoML and the emerging approach of declarative ML help simplify the process of creating and refining ML models.
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ABSTRACT :
The modern data stack must be automated, low code/no code, AI-assisted, graph-enabled, multimodal, streaming, distributed, meshy, converged, polyglot,...
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ABSTRACT :
This blog recommends four guiding principles for effective data engineering in a lakehouse environment.
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ABSTRACT :
This blog explores the opportunity for automated workflows to help cross-functional teams collaborate and standardize organizational master data.
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ABSTRACT :
The data pipeline market comprises four segments: data ingestion, data transformation, DataOps, and orchestration. This blog defines three principles...
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