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

Smarten

MAY 11, 2017

Advanced Data Discovery ensures data democratization by enabling users to drastically reduce the time and cost of analysis and experimentation. Plug n’ Play Predictive Analysis enables business users to explore power of predictive analytics without indepth understanding of statistics and data science.

Experimentation 49

Experimentation Visualization Business Intelligence Predictive Analytics 49

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 Experimentation Reporting 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

Corinium

APRIL 25, 2019

For example auto insurance companies offering to capture real-time driving statistics from policy-holders’ cars to encourage and reward safe driving. What are you most looking forward to about CDAOI Insurance 2019? And more recently, we have also seen innovation with IOT (Internet Of Things).

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Domino Data Lab

MAY 8, 2019

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. Jupyter Book: Interactive books running in the cloud ” by Chris Holdgraf (2019-03-27).

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105