Domino Data Lab

SEPTEMBER 25, 2019

A big part of statistics, particularly for financial and econometric data, is analyzing time series, data that are autocorrelated over time. Fortunately, the forecast package has a number of functions to make working with time series data easier, including determining the optimal number of diffs. The result is shown in Figure 24.4. >

Forecasting 87

Forecasting Modeling Statistics Optimization 87

bridgei2i

MAY 26, 2020

You know the markets shake and the accompanying Swine Flu epidemic of 2015 and 2016, the Japanese tsunami and the Thailand floods in 2011 that shook up the high-tech value chain quite a bit, the great financial crisis and the accompanying H1N1 outbreak in 2008-2009, MERS and SARS before that in 2003. As the crisis evolved.

Enterprise 131

Enterprise Management Forecasting Manufacturing 131

Smarten

SEPTEMBER 6, 2019

In the meantime, business users have a tool that is sophisticated enough to present clear, accurate, measurable results and allow them to find the source of problems, optimize results and share data to support business decisions.

Analytics 53

Analytics IT Business Intelligence Testing 53

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

On the one hand, basic statistical models (e.g. The first is that they are straightforward to optimize using traditional gradient-based optimizers as long as we pre-specify the placement of the knots. There is a robust set of tools for working with these kinds of constrained optimization problems. Pfeifer, J., Pfeifer, J.

Machine Learning 111

Machine Learning Deep Learning Modeling Interactive 111

Rita Sallam

JULY 22, 2016

Gartner revamped the BI and Analytics Magic Quadrant in 2016 to reflect the mainstreaming of this market disruption. A modern BI platform supports IT-enabled analytic content development. Again, check out the Critical Capabilities for BI and Analytic Platforms for how each vendor compares.

Analytics 40

Analytics Business Intelligence Metadata Statistics 40

The Unofficial Google Data Science Blog

MARCH 31, 2016

We often use statistical models to summarize the variation in our data, and random effects models are well suited for this — they are a form of ANOVA after all. Journal of the American Statistical Association 68.341 (1973): 117-130. [5] Journal of the American Statistical Association, Vol. bandit problems). 7] Nicholas A. "A

Modeling 40

Modeling Statistics Advertising Testing 40

Smarten

SEPTEMBER 9, 2024

In fact, the world-renowned technology research firm, Gartner, first introduced the concept in 2016. Gartner defines a citizen data scientist as, ‘ a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics.’

Consulting 52

Consulting Cost-Benefit Data Science Business Intelligence 52

Domino Data Lab

AUGUST 22, 2019

Although it’s not perfect, [Note: These are statistical approximations, of course!] You can home in on an optimal value by specifying, say, 32 dimensions and varying this value by powers of 2. If we were using CBOW, then a window size of 5 (for a total of 10 context words) could be near the optimal value. Example 11.6

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Andrew White

JANUARY 9, 2022

– We did some early work a few years ago that look at the career path of a CDO – see from 2016 Build Your Career Path to the Chief Data Officer Role. This was not statistic and we have not really explored this in any greater detail since. 2016) though I have followed the topic in retail and CPG for years.

Analytics 64

Analytics Measurement Data-driven Modeling 64

O'Reilly on Data

MARCH 23, 2021

Just as the newspaper page has historically been a mish-mash collection of movie ads, obituaries, and opinions stitched together in a way that made the most business and economic sense for any given publisher, your Facebook feed is driven by a collection of algorithms that, in the end, are optimizing for growth and revenue. Footnotes.

Internet Publishing and Broadcasting 342

Internet Publishing and Broadcasting Broadcasting Data-driven Publishing 342

Domino Data Lab

JULY 1, 2021

statistical model-based techniques – Using Machine Learning we can streamline and simplify the process of building NER models, because this approach does not need a predefined exhaustive set of naming rules. The process of statistical learning can automatically extract said rules from a training dataset. The CRF model.

Modeling 111

Modeling Statistics Testing Metrics 111

Occam's Razor

SEPTEMBER 13, 2016

Econsultancy/Lynchpin provides this description in the report: "There were 960 respondents to our research request, which took the form of a global online survey fielded in May and June 2016. Take this as an example… How do you know that this is a profoundly sub-optimal collection of choices to provide?

Modeling 128

Modeling Reporting Strategy Consulting 128

Smarten

MARCH 20, 2025

In 2016, the technology research firm, Gartner, coined the term Citizen Data Scientist, and defined it as a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics.

Prescriptive Analytics 64

Prescriptive Analytics Advertising Data-driven Statistics 64

Occam's Razor

JULY 13, 2017

This is the simple view that greets you, outbreaks from 1890 to 2016 with vaccine development during that same time…. Consider this, conversion rate could go up by a statistically significant percentage… While revenue actually goes down. But how does the time taken to develop vaccines compare to the speed and frequency of outbreaks?

Visualization 125

Visualization Strategy Interactive Statistics 125