Domino Data Lab

JUNE 23, 2019

Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. Yet, this challenge is not insurmountable. for what is and isn’t possible) to address these challenges. Transcript.

Management 110

Management Machine Learning Experimentation Metrics 110

Occam's Razor

SEPTEMBER 19, 2011

You need people with deep skills in Scientific Method , Design of Experiments , and Statistical Analysis. Then they isolated regions of the country (by city, zip, state, dma pick your fave) into test and control regions. People in the test regions will participate in our hypothesis testing. ask for a raise.

Measurement 119

Measurement Advertising Testing Marketing 119

Domino Data Lab

OCTOBER 2, 2019

As data science work is experimental and probabilistic in nature, data scientists are often faced with making inferences. The case that might be familiar to you is an AB test. You can make a change to a product and test it against the original version of the product. A complementary Domino project is available. . Introduction.

Machine Learning 68

Machine Learning Measurement Modeling Testing 68

Domino Data Lab

MAY 8, 2019

In contrast, some researchers who are exploring the definitions, possibilities, and limitations of model interpretation point toward more comprehensive views. There’s no one-size-fits-all definition of what’s required across all verticals. Let’s look at two issues, both more social than technical, that bubble to the top of the list.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Occam's Razor

APRIL 8, 2013

Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. Testing out a new feature. Identify, hypothesize, test, react. But at the same time, they had to have a real test of an actual feature. You don’t need a beautiful beast to go out and test.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

Ontotext

APRIL 3, 2024

Nimit Mehta: I think that 2024 is going to be a buckle-down year, but, at the same time, we’ll see a rapid explosion of experimentation. ” So, maybe they are open to some testing and exploration, but when it’s prime time, larger organizations won’t run the risk of putting something untested. These are not statistical inferences.

Technology 59

Technology Risk Digital Transformation Measurement 59

Occam's Razor

JUNE 4, 2018

I mean developing and inserting a subtle collection of gentle nudges that can help increase the conversion rate by a statistically significant amount. Nudging has plenty of different definitions. Such is the case with A/B testing. I don’t mean: BUY IT NOW OR ELSE! Sizing the Opportunity. Welcome to Nudging.

Strategy 124

Strategy Cost-Benefit Testing Sales 124

The Unofficial Google Data Science Blog

OCTOBER 21, 2015

The beliefs of this community are always evolving, and the process of thoughtfully generating, testing, refuting and accepting ideas looks a lot like Science. By definition, it is hard to disentangle causes and effects in these settings because it is rarely possible to isolate all relevant factors.

Slice and Dice 45

Slice and Dice Experimentation Data-driven Data Science 45

Occam's Razor

JUNE 6, 2007

Bonus: Interactive CD: Contains six podcasts, one video, two web analytics metrics definitions documents and five insightful powerpoint presentations. Experimentation & Testing (A/B, Multivariate, you name it). What ideas to test first on your site? It is a book about Web Analytics 2.0. Qualitative and quantitative.

Analytics 60

Analytics Metrics Marketing Dashboards 60

O'Reilly on Data

DECEMBER 9, 2019

We develop an ordinary least squares (OLS) linear regression model of equity returns using Statsmodels, a Python statistical package, to illustrate these three error types. We use the diagnostic test results of our regression model to support the reasons why CIs should not be used in financial data analyses. and an error term ??

Statistics 27

Statistics Uncertainty Risk Marketing 27

Occam's Razor

MARCH 23, 2010

Part of it is fueled by a vocal minority genuinely upset that 10 years on we are still not a statistically powered bunch doing complicated analysis that is shifting paradigms. Because every tool uses its own sweet metrics definitions, cookie rules, session start and end rules and so much more. Usually at least a test.

Analytics 118

Analytics Consulting Metrics Experimentation 118