Data Processing Experimentation Metrics Testing 
AWS Big Data
AUGUST 21, 2023
For the demo, we’re using the Amazon Titan foundation model hosted on Amazon Bedrock for embeddings, with no fine tuning. It similarly codes the query as a vector and then uses a distance metric to find nearby vectors in the multi-dimensional space. With OpenSearch’s Search Comparison Tool , you can compare the different approaches.
Occam's Razor
MAY 22, 2006
This post is a primer on the delightful world of testing and experimentation (A/B, Multivariate, and a new term from me: Experience Testing). Experimentation and testing help us figure out we are wrong, quickly and repeatedly and if you think about it that is a great thing for our customers, and for our employers.
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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.
AWS Big Data
MAY 2, 2023
If your updates to a dataset triggers multiple subsequent DAGs, then you can use the Airflow metric max_active_tasks_per_dag to control the parallelism of the consumer DAG and reduce the chance of overloading the system. The workflow steps are as follows: The producer DAG makes an API call to a publicly hosted API to retrieve data.
DataRobot
JUNE 10, 2021
Traditionally, experimentation and observation was the only way to understand the physical-chemical properties of the molecule. To foster innovation in this area, AICrowd hosted a competition to predict the olfactory properties of a molecule. DataRobot also provides per-label metrics so that metrics per class can be compared.
AWS Big Data
JANUARY 9, 2024
It similarly codes the query as a vector and then uses a distance metric to find nearby vectors in the multi-dimensional space to find matches. This functionality was initially released as experimental in OpenSearch Service version 2.4, This is also called embedding the text into the vector space.
DataRobot Blog
JANUARY 10, 2023
ML model builders spend a ton of time running multiple experiments in a data science notebook environment before moving the well-tested and robust models from those experiments to a secure, production-grade environment for general consumption. A host of open-source libraries. Deep Dive into DataRobot Notebooks. Auto-scale compute.
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