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

O'Reilly on Data

MARCH 31, 2020

All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. The need for an experimental culture implies that machine learning is currently better suited to the consumer space than it is to enterprise companies.

Management 332

Management Machine Learning Experimentation Metrics 332

FineReport

DECEMBER 19, 2019

If you want to learn more about self-service BI tools, you can take a look at this review: 5 Most Popular Business Intelligence (BI) Tools in 2019 , to understand your own needs and then choose the tool that is right for you. Of course, other BI tools such as Power BI and Qlikview also have their own advantages. From Google.

Knowledge Discovery 98

Knowledge Discovery Visualization Reporting Experimentation 98

Domino Data Lab

JANUARY 24, 2019

Before we get too far into 2019, I wanted to take a brief moment to reflect on some of the changes we’ve seen in the market. 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.

Data Science 65

Data Science Marketing Data-driven Statistics 65

Business Over Broadway

MAY 22, 2019

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. So, become data literate.

Machine Learning 40

Machine Learning Technology Digital Transformation Data Science 40

O'Reilly on Data

MARCH 18, 2020

The new survey, which ran for a few weeks in December 2019, generated an enthusiastic 1,388 responses. This year, about 15% of respondent organizations are not doing anything with AI, down ~20% from our 2019 survey. It seems as if the experimental AI projects of 2019 have borne fruit. But what kind?

Enterprise 311

Enterprise Deep Learning Data Governance Risk 311

Jet Global

APRIL 27, 2023

Understand Your Research and Development Manufacturing accounted for 58 percent of US domestic research and development (R&D) spending in 2019, according to the  National Center for Science and Engineering Statistics. That  That means tax law changes to R&D investment are a major concern in the industry.

Manufacturing 52

Manufacturing Marketing Reporting Experimentation 52