AWS Big Data

MAY 2, 2023

The workflow steps are as follows: The producer DAG makes an API call to a publicly hosted API to retrieve data. Test the feature To test this feature, run the producer DAG. Removal of experimental Smart Sensors. Test the feature Upload the four sample text files from the local data folder to an S3 bucket data folder.

Testing 103

Testing Experimentation Management Metadata 103

O'Reilly on Data

MARCH 31, 2020

But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools. This has serious implications for software testing, versioning, deployment, and other core development processes.

Management 332

Management Machine Learning Experimentation Metrics 332

AWS Big Data

JANUARY 9, 2024

Now users seek methods that allow them to get even more relevant results through semantic understanding or even search through image visual similarities instead of textual search of metadata. This functionality was initially released as experimental in OpenSearch Service version 2.4, and is now generally available with version 2.9.

Cost-Benefit 95

Cost-Benefit Visualization Modeling Machine Learning 95

AWS Big Data

JULY 26, 2023

This enables you to process a user’s query to find the closest vectors and combine them with additional metadata without relying on external data sources or additional application code to integrate the results. You can choose to host your collection on a public endpoint or within a VPC.

Metadata 52

Metadata Cost-Benefit Testing Metrics 52

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. One of the longer-term trends that we’re seeing with Airflow , and so on, is to externalize graph-based metadata and leverage it beyond the lifecycle of a single SQL query, making our workflows smarter and more robust. BTW, videos for Rev2 are up: [link].

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Cloudera

JUNE 6, 2019

The typical Cloudera Enterprise Data Hub Cluster starts with a few dozen nodes in the customer’s datacenter hosting a variety of distributed services. While this approach provides isolation, it creates another significant challenge: duplication of data, metadata, and security policies, or ‘split-brain’ data lake.

Metadata 85

Metadata Data Lake Optimization Strategy 85