Remove 2018 Remove Experimentation Remove Modeling Remove Statistics
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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

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. Figure 2: Spreading measurements out makes estimates of model (slope of line) more accurate. And sometimes even if it is not[1].)

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Reflections on the Data Science Platform Market

Domino Data Lab

In 2018 we saw the “data science platform” market rapidly crystallize into three distinct product segments. These solutions help data analysts build models by automating tasks in data science, including training models, selecting algorithms, and creating features. Reflections. Jupyter) or IDEs (e.g.,

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AI Adoption in the Enterprise 2021

O'Reilly on Data

Relatively few respondents are using version control for data and models. Tools for versioning data and models are still immature, but they’re critical for making AI results reproducible and reliable. The biggest skills gaps were ML modelers and data scientists (52%), understanding business use cases (49%), and data engineering (42%).

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Customer Experience and Emerging Technologies: My CXChat Summary on Artificial Intelligence, Machine Learning and the Customer

Business Over Broadway

For those of you who are interested, here is Gartner’s latest (2018) hype cycle on emerging technologies. According to Gartner, companies need to adopt these practices: build culture of collaboration and experimentation; start with a 3-way partnership among executives leading digital initiative, line of business and IT.

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Defining data science in 2018

Data Science and Beyond

Two years later, I published a post on my then-favourite definition of data science , as the intersection between software engineering and statistics. This article is a short summary of my understanding of the definition of data science in 2018. Even better – I still get paid for being a data scientist. But what does it mean?

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The Impact Matrix | A Digital Analytics Strategic Framework

Occam's Razor

work (collection, processing, reporting, analysis), processes, org structure, governance models, last-mile gaps , metrics ladders of awesomeness , and… so… much… more. Remember, tools, work, processes, org structure, governance models, last-mile gaps, metrics ladders of awesomeness, and… so… much… more. The Implications of Complexity.

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Six Nudges: Creating A Sense Of Urgency For Higher Conversion Rates!

Occam's Razor

It is 2018—why are there still light gray below-the-fold add to cart buttons? I mean developing and inserting a subtle collection of gentle nudges that can help increase the conversion rate by a statistically significant amount. Not easy, but your business model has to change to survive.). youarekillingme.

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