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The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

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.

Metrics 156
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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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Teaching AI to Smell by Using DataRobot

DataRobot

Traditionally, experimentation and observation was the only way to understand the physical-chemical properties of the molecule. It was introduced in 1980 but open-sourced in 2007, which created its widespread use. DataRobot also provides per-label metrics so that metrics per class can be compared.

Metrics 52
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Knowledge

Occam's Razor

" ~ Web Metrics: "What is a KPI? " + Standard Metrics Revisited Series. "Engagement" Is Not A Metric, It's An Excuse. Defining a "Master Metric", + a Framework to Gain a Competitive Advantage in Web Analytics. The Awesome Power of Visualization 2 -> Death and Taxes 2007.

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Experiment design and modeling for long-term studies in ads

The Unofficial Google Data Science Blog

Nevertheless, A/B testing has challenges and blind spots, such as: the difficulty of identifying suitable metrics that give "works well" a measurable meaning. accounting for effects "orthogonal" to the randomization used in experimentation. accounting for effects "orthogonal" to the randomization used in experimentation.

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To Balance or Not to Balance?

The Unofficial Google Data Science Blog

In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects. 2007): Propose a finite collection $mathcal L={hat e_k:k=1,ldots,K}$ of estimation algorithms. This is often referred to as the positivity assumption.

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Themes and Conferences per Pacoid, Episode 6

Domino Data Lab

Spoiler alert: a research field called curiosity-driven learning is emerging at the nexis of experimental cognitive psychology and industry use cases for machine learning, particularly in gaming AI. Ensure a culture that supports a steady process of learning and experimentation. Frédéric Kaplan, Pierre-Yves Oudeyer (2007).