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Experiment design and modeling for long-term studies in ads

The Unofficial Google Data Science Blog

by HENNING HOHNHOLD, DEIRDRE O'BRIEN, and DIANE TANG In this post we discuss the challenges in measuring and modeling the long-term effect of ads on user behavior. Nevertheless, A/B testing has challenges and blind spots, such as: the difficulty of identifying suitable metrics that give "works well" a measurable meaning.

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MLOps and the evolution of data science

IBM Big Data Hub

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.

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A Guide To Starting A Career In Business Intelligence & The BI Skills You Need

datapine

According to the US Bureau of Labor Statistics, demand for qualified business intelligence analysts and managers is expected to soar to 14% by 2026, with the overall need for data professionals to climb to 28% by the same year. The Bureau of Labor Statistics also states that in 2015, the annual median salary for BI analysts was $81,320.

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Mobile Marketing 2015: Rethink Customer Acquisition, Intent Targeting

Occam's Razor

Two companies, Skullcandy and TripIt, delivering on four amazing outcomes that inspire us to set the bar significantly higher for our mobile efforts in 2015 (or sooner!). I'm sure you are impressed at the data mining and intent targeting efforts of TripIt. That is what all marketing in 2015 will look like.

Marketing 144
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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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Magnificent Mobile Website And App Analytics: Reports, Metrics, How-to!

Occam's Razor

But why blame others, in this post let's focus on one important reason whose responsibility can be squarely put on your shoulders and mine: Measurement. Create a distinct mobile website and mobile app measurement strategies. Mobile content consumption, behavior along key metrics (time, bounces etc.)

Metrics 141
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Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

Because of its architecture, intrinsically explainable ANNs can be optimised not just on its prediction performance, but also on its explainability metric. but it generally relies on measuring the entropy in the change of predictions given a perturbation of a feature. 2015) for additional details. See Wei et al. Bahdanau, D.,

Modeling 139