Remove 2013 Remove Experimentation Remove Measurement Remove Metrics
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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

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., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.

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The AIgent: Using Google’s BERT Language Model to Connect Writers & Representation

Insight

In 2013, Robert Galbraith?—?an One way that we can get around this is to use the proportion of tags that fall into a given class as a measure of our degree of confidence in that class association. Future versions of the AIgent may be improved with the use of more nuanced metrics, depending on the class-encoding scheme applied.

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Eight Silly Data Things Marketing People Believe That Get Them Fired.

Occam's Razor

[A benchmark for you: In 2013 if 30% of your time, Ms./Mr. Many used some data, but they unfortunately used silly data strategies/metrics. And silly simply because as soon as the strategy/success metric being obsessed about was mentioned, it was clear they would fail. It is a really good metric. They get you fired.

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