2018 Data-driven Experimentation Statistics 
Domino Data Lab
JANUARY 24, 2019
In 2018 we saw the “data science platform” market rapidly crystallize into three distinct product segments. Over the last couple years, it would be hard to blame anyone for being overwhelmed looking at the data science platform market landscape. Proprietary (often GUI-driven) data science platforms.
The Unofficial Google Data Science Blog
APRIL 23, 2024
If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. Modeling live experiment data Data scientists at YouTube are rarely involved in the analysis of typical live traffic experiments.
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O'Reilly on Data
APRIL 19, 2021
During the first weeks of February, we asked recipients of our Data & AI Newsletter to participate in a survey on AI adoption in the enterprise. The second-most significant barrier was the availability of quality data. Relatively few respondents are using version control for data and models. Respondents.
Occam's Razor
JULY 24, 2018
The result is analytical strategies that are uninformed by reality, and driven new tool features, random expert recommendations and shiny objects ( OMG we have to get offline attribution! ). Diving a bit deeper into the x-axis… While most data can be collected in real-time now, not all metrics are useful in real-time.
Domino Data Lab
MAY 8, 2019
For example, common practices for collecting data to build training datasets tend to throw away valuable information along the way. The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. 2018-06-21). ML model interpretability and data visualization.
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