DataRobot Blog

APRIL 29, 2022

This provides a great amount of benefit, but it also exposes institutions to greater risk and consequent exposure to operational losses. The stakes in managing model risk are at an all-time high, but luckily automated machine learning provides an effective way to reduce these risks.

Risk 111

Risk Modeling IT Risk Management 111

The Unofficial Google Data Science Blog

APRIL 17, 2017

In the first plot, the raw weekly actuals (in red) are adjusted for a level change in September 2011 and an anomalous spike near October 2012. Such a model risks conflating important aspects, notably the growth trend, with other less critical aspects.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

Occam's Razor

JUNE 4, 2018

I mean developing and inserting a subtle collection of gentle nudges that can help increase the conversion rate by a statistically significant amount. Go to the Multi-Channel Funnels folder in Google analytics and look at two other yummy reports: Time Lag and Path Length. I don’t mean: BUY IT NOW OR ELSE! Sizing the Opportunity.

Strategy 124

Strategy Cost-Benefit Testing Sales 124

Domino Data Lab

JANUARY 6, 2019

What are the projected risks for companies that fall behind for internal training in data science? Recently the World Economic Forum published “ The Future of Jobs Report 2018.” Another recent report by McKinsey Global Institute correlates closely with the WEF analysis. In business terms, why does this matter ?

Data Science 56

Data Science Machine Learning Reporting Visualization 56

Peter James Thomas

AUGUST 12, 2018

Integrity of statistical estimates based on Data. Having spent 18 years working in various parts of the Insurance industry, statistical estimates being part of the standard set of metrics is pretty familiar to me [7]. The thing with statistical estimates is that they are never a single figure but a range. million ± £0.5

Metrics 49

Metrics Statistics Data Quality Measurement 49

datapine

AUGUST 29, 2022

He founded the project Apache Storm in 2011, which turned to be “one of the world’s most popular stream processors and has been adopted by many of the world’s largest companies, including Yahoo!, Microsoft, Alibaba, Taobao, WebMD, Spotify, Yelp” according to Marz himself. It was lately revised and updated in January 2016.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Domino Data Lab

MARCH 3, 2019

We had big surprises at several turns and have subsequently published a series of reports. Let’s look through some of the insights gained from those reports. Seriously, this entire article merely skims the surface of those reports. Mature practices reported 86%, and within financial services the numbers were somewhat higher.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49