Data Collection Testing Uncertainty 
O'Reilly on Data
MARCH 31, 2020
Machine learning adds uncertainty. The model outputs produced by the same code will vary with changes to things like the size of the training data (number of labeled examples), network training parameters, and training run time. Underneath this uncertainty lies further uncertainty in the development process itself.
Jet Global
DECEMBER 10, 2020
To implement AI, you need four main resources: an algorithm, at least 15 years of data, massive amounts of data over that time period, and a way to test the algorithm and get feedback on its accuracy. It’s part of a mixed bag of tools that we use for data collection, tracking, reporting, and analysis.
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Domino Data Lab
MAY 15, 2019
The last step for a PM is to “use derived data from the system to build new products” as this provides another way to ensure ROI across the business. Addressing the Uncertainty that ML Adds to Product Roadmaps. Here, Pete outlines common challenges and key questions for PMs to consider.
CIO Business Intelligence
JULY 17, 2023
Picture years and years of paper Until recently, ZEISS’s highly regulated manufacturing environment relied heavily on two documentation types: Digital History Records (DHR) to validate data for compliance and Work Instruction documentation to stipulate the required steps in performing specific activities. Reams of it, in fact.
Occam's Razor
APRIL 8, 2013
We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. Testing out a new feature.
CIO Business Intelligence
APRIL 28, 2024
However, new energy is restricted by weather and climate, which means extreme weather conditions and unpredictable external environments bring an element of uncertainty to new energy sources. communication reliability, which supports minute-level data collection and second-level control for low-voltage transparency.
CIO Business Intelligence
JUNE 28, 2022
Some of the paradoxes relate to the practical challenges of gathering and organizing so much data. Others are philosophical, testing our ability to reason about abstract qualities. And then there is the rise of privacy concerns around so much data being collected in the first place.
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