2015 Knowledge Discovery Testing 
The Unofficial Google Data Science Blog
OCTOBER 7, 2015
A/B testing is used widely in information technology companies to guide product development and improvements. For questions as disparate as website design and UI, prediction algorithms, or user flows within apps, live traffic tests help developers understand what works well for users and the business, and what doesn’t.
The Unofficial Google Data Science Blog
JULY 22, 2020
Another reason to use ramp-up is to test if a website's infrastructure can handle deploying a new arm to all of its users. The website wants to make sure they have the infrastructure to handle the feature while testing if engagement increases enough to justify the infrastructure. We offer two examples where this may be the case.
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The Unofficial Google Data Science Blog
NOVEMBER 4, 2015
One way to check $f_theta$ is to gather test data and check whether the model fits the relationship between training and test data. This tests the model’s ability to distinguish what is common for each item between the two data sets (the underlying $theta$) and what is different (the draw from $f_theta$).
Domino Data Lab
AUGUST 1, 2021
After forming the X and y variables, we split the data into training and test sets. 2015) for additional details. Next, we pick a sample that we want to get an explanation for, say the first sample from our test dataset (sample id 0). For sample 23 from the test set, the model is leaning towards a bad credit prediction.
CIO Business Intelligence
MARCH 26, 2025
Search and knowledge discovery technology is required for organizations to uncover, analyze, and utilize key data. Now, a new wave of AI generative AI (GenAI) is changing how forward-looking organizations approach search, knowledge management, and other forms of knowledge discovery. How did we get here?
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