The Unofficial Google Data Science Blog

APRIL 19, 2021

To explain, let’s borrow a quote from Nate Silver’s The Signal and the Noise : One of the most important tests of a forecast — I would argue that it is the single most important one — is called calibration. isn’t good enough: it optimizes the calibration term, but pays the price in sharpness. This shows why $Pr(mathrm{Spam}) = 0.1$

Modeling 122

Modeling IT Metrics Testing 122

Sisense

MAY 12, 2019

DevOps first came about in 2007-2008 to fix problems in the software industry and bring with it continuous improvement and greater efficiencies. In this case, insights that can be responded to in order to optimize a sequence or a larger process quickly. But is that really true? Is your DevOps movement doing what it was set out to do?

Analytics 79

Analytics Dashboards KPI Measurement 79

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

A/B testing is used widely in information technology companies to guide product development and improvements. For questions as disparate as website design and UI, prediction algorithms, or user flows within apps, live traffic tests help developers understand what works well for users and the business, and what doesn’t.

Modeling 63

Modeling Experimentation Knowledge Discovery Testing 63

The Unofficial Google Data Science Blog

JUNE 30, 2016

A naïve way to solve this problem would be to compare the proportion of buyers between the exposed and unexposed groups, using a simple test for equality of means. It should be noted that inverse probability weighting is not generally optimal (i.e., the curse of dimensionality). Here $c(x)$ is any function of $x$.

Statistics 45

Statistics Optimization Modeling Experimentation 45

Occam's Razor

OCTOBER 15, 2012

I spend 70% of my time in the US and for those discussions I'm primary looking at speed (connection above), mobile penetration (yes, 2007 was the year of mobile!), Drive overall business outcomes by combining online and offline consumer touch points optimally. and mobile intent to purchase (I love this data).

Advertising 137

Advertising Marketing Strategy Insurance 137

Occam's Razor

FEBRUARY 7, 2011

Alex Cohen: How to optimize with sparse data! Strategic "how can we" questions: Simon: How to "sell" GWO testing (+Analytics) to Managers, very limited time/budget/staffing (btw, we already use Analytics and Adwords, but GWO is proving harder to get prioritised and understood, maybe worry of complexity). or non-U.S.),

Analytics 94

Analytics Measurement Metrics Predictive Analytics 94

The Unofficial Google Data Science Blog

JULY 22, 2020

Another reason to use ramp-up is to test if a website's infrastructure can handle deploying a new arm to all of its users. The website wants to make sure they have the infrastructure to handle the feature while testing if engagement increases enough to justify the infrastructure. We offer two examples where this may be the case.

Experimentation 96

Experimentation Statistics Testing Knowledge Discovery 96

Edwin Chen

MARCH 13, 2011

This is a summary of Bell and Koren’s 2007 Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights paper. We’ll see how using an optimization method to derive weights (as opposed to deriving weights via a similarity function) overcomes these two limitations. But how do I choose this weight?

Optimization 40

Optimization Modeling Cost-Benefit Measurement 40

CIO Business Intelligence

OCTOBER 29, 2024

since 2007. These include a business focus on ethics, AI data optimization for trustworthy outcomes, energy-efficient technology and application principles centered on UX and accessibility for all. Cost and resource optimization Cost efficiency. Is your IT sustainable? Resource utilization.

Enterprise 122

Enterprise Cost-Benefit Metrics Strategy 122