The Unofficial Google Data Science Blog

APRIL 23, 2024

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. And we can keep repeating this approach, relying on intuition and luck. Why experiment with several parameters concurrently?

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Data Science and Beyond

JULY 22, 2018

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?

Data Science 79

Data Science Machine Learning Statistics Predictive Modeling 79

Domino Data Lab

JANUARY 24, 2019

In 2018 we saw the “data science platform” market rapidly crystallize into three distinct product segments. This group of solutions targets code-first data scientists who use statistical programming languages and spend their days in computational notebooks (e.g., Reflections. Code-first data science platforms. Jupyter) or IDEs (e.g.,

Data Science 65

Data Science Marketing Data-driven Statistics 65

CIO Business Intelligence

AUGUST 21, 2024

Starting in 2018, the agency used agents, in the form of Raspberry PI computers running biologically-inspired neural networks and time series models, as the foundation of a cooperative network of sensors. But multiagent AI systems are still in the experimental stages, or used in very limited ways. It’s a system still being used today.

Risk 136

Risk Insurance Cost-Benefit Software 136

O'Reilly on Data

APRIL 19, 2021

We’ll look at this later, but being able to reproduce experimental results is critical to any science, and it’s a well-known problem in AI. In contrast, in our 2018 report, Asia was behind in mature practices, though it had a markedly higher number of respondents in the “early adopter” or “exploring” stages. Bottlenecks to AI adoption.

Enterprise 358

Enterprise Risk Modeling Manufacturing 358

Business Over Broadway

MAY 22, 2019

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.

Machine Learning 40

Machine Learning Technology Digital Transformation Data Science 40

Domino Data Lab

MAY 8, 2019

2018-06-21). They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have. Use of influence functions goes back to the 1970s in robust statistics. Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105