Metrics Reporting Testing Uncertainty 
O'Reilly on Data
JUNE 15, 2023
If we want prosocial outcomes, we need to design and report on the metrics that explicitly aim for those outcomes and measure the extent to which they have been achieved. If every company had a different way of reporting its finances, it would be impossible to regulate them. There is no simple way to solve the alignment problem.
The Unofficial Google Data Science Blog
DECEMBER 14, 2021
by AMIR NAJMI & MUKUND SUNDARARAJAN Data science is about decision making under uncertainty. Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
DataKitchen
SEPTEMBER 21, 2023
Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability In a world where 97% of data engineers report burnout and crisis mode seems to be the default setting for data teams, a Zen-like calm feels like an unattainable dream. One of the primary sources of tension?
The Unofficial Google Data Science Blog
APRIL 23, 2024
the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Crucially, it takes into account the uncertainty inherent in our experiments. Here, $X$ is a vector of tuning parameters that control the system's operating characteristics (e.g.
Occam's Razor
APRIL 8, 2013
To win in business you need to follow this process: Metrics > Hypothesis > Experiment > Act. 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. That metric is tied to a KPI.
O'Reilly on Data
OCTOBER 13, 2020
In Bringing an AI Product to Market , we distinguished the debugging phase of product development from pre-deployment evaluation and testing. To support verification in these areas, a product manager must first ensure that the AI system is capable of reporting back to the product team about its performance and usefulness over time.
Smart Data Collective
AUGUST 18, 2021
Although widely used, keyword scanning software alone simply doesn’t generate sufficient success metrics when sifting through candidate resumes. So, in this situation, you may devise and implement an online test designed to assess candidates on their basic skills and knowledge of their field of work. Speed up the recruitment process.
Expert insights. Personalized for you.
292 
Let's personalize your content