The Unofficial Google Data Science Blog

APRIL 23, 2024

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.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Data Science and Beyond

APRIL 5, 2021

I’ve been working remotely with Automattic since 2017, so I was pretty covid-ready as far as work was concerned. My main "day job" focus in 2020 was on being the tech lead for Automattic’s new experimentation platform (ExPlat). Remote work. This aligns well with my long-standing interest in causal inference.

Experimentation 61

Experimentation Testing Publishing Measurement 61

CIO Business Intelligence

MAY 16, 2023

It surpasses blockchain and metaverse projects, which are viewed as experimental or in the pilot stage, especially by established enterprises. higher [in 2022] than in 2017.” AI surpassed other technologies in conversations about innovation The research underscores that AI is leading the way in accelerating innovation.

Advertising 92

Advertising Recreation/Entertainment Experimentation Enterprise 92

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 95

Experimentation Statistics Testing Strategy 95

O'Reilly on Data

MARCH 23, 2023

All of these models are based on a technology called Transformers , which was invented by Google Research and Google Brain in 2017. It’s by far the most convincing example of a conversation with a machine; it has certainly passed the Turing test. That’s either the most or the least important question to ask.

IT 262

IT Modeling Testing Risk 262

Domino Data Lab

MAY 8, 2019

Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV. Adrian Weller (2017-07-29). “ They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have. Challenges for Transparency ”. Riccardo Guidotti, et al.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

JULY 2, 2019

For more background about program synthesis, check out “ Program Synthesis Explained ” by James Bornholt from 2015, as well as the more recent “ Program Synthesis in 2017-18 ” by Alex Polozov from 2018. A Program Synthesis Primer ” – Aws Albarghouthi (2017-04-24). A Program Synthesis Primer ” – Aws Albarghouthi (2017-04-24).

Metadata 105

Metadata Machine Learning Data Science Data-driven 105