Remove 2015 Remove Experimentation Remove Reporting
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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

To find optimal values of two parameters experimentally, the obvious strategy would be to experiment with and update them in separate, sequential stages. Our experimentation platform supports this kind of grouped-experiments analysis, which allows us to see rough summaries of our designed experiments without much work.

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6 enterprise DevOps mistakes to avoid

CIO Business Intelligence

Driven by the development community’s desire for more capabilities and controls when deploying applications, DevOps gained momentum in 2011 in the enterprise with a positive outlook from Gartner and in 2015 when the Scaled Agile Framework (SAFe) incorporated DevOps.

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AI on the mainframe? IBM may be onto something

CIO Business Intelligence

billion in 2015 to less than $6.5 It’s a natural fit and will be interesting to see how these ensemble AI models work and what use cases will go from experimentation to production,” says Dyer. LLMs can drive significant insights in compliance, regulatory reporting, risk management, and customer service automation in financial services.

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Drug Discovery Needs AI To Discover More Treatments

Smart Data Collective

In a report on the failure rates of drug discovery efforts between 2013 and 2015, Richard K. To bring costs down and encourage further experimentation, artificial intelligence can study hundreds or thousands of patient records in search of the biomarkers the drug intends to target.

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Magnificent Mobile Website And App Analytics: Reports, Metrics, How-to!

Occam's Razor

Dive into Mobile Reporting and Analysis. Dive into Mobile Reporting and Analysis. Media-Mix Modeling/Experimentation. Dive into Mobile Reporting and Analysis. What do you learn from this report? What do you learn from this report? What do you learn from this report? Tag your mobile website.

Metrics 143
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The 2015 Digital Marketing Rule Book. Change or Perish.

Occam's Razor

Allocate some of your aforementioned 15% budget to experimentation and testing. Let me just say this… more of marketing is becoming algorithmically driven and a lot more decisions we make using reports today are being automated to be made faster, more efficiently, on our behalf. The 2015 Digital Marketing Rule Book.

Marketing 142
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Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

Instead, we focus on the case where an experimenter has decided to run a full traffic ramp-up experiment and wants to use the data from all of the epochs in the analysis. When there are changing assignment weights and time-based confounders, this complication must be considered either in the analysis or the experimental design.