DataRobot Blog

MAY 26, 2022

When the FRB’s guidance was first introduced in 2011, modelers often employed traditional regression -based models for their business needs. Figure 4: DataRobot provides an interactive ROC curve specifying relevant model performance metrics on the bottom right.

Risk 52

Risk Modeling Metrics Business Objectives 52

Domino Data Lab

AUGUST 22, 2019

Although it’s not perfect, [Note: These are statistical approximations, of course!] We need to take a brief break from natural language-specific content here to introduce a metric that will come in handy in the next section of the chapter, when we will evaluate the performance of deep learning NLP models. Note: Maas, A., Example 11.6

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

The Unofficial Google Data Science Blog

MAY 31, 2016

This means it is possible to specify exactly in which geos an ad campaign will be served – and to observe the ad spend and the response metric at the geo level. In other words, iROAS is the slope of a curve of the response metric plotted against the underlying advertising spend. They are non-overlapping geo-targetable regions.

Advertising 43

Advertising Testing Sales Statistics 43

Domino Data Lab

MARCH 3, 2019

What metrics are used to evaluate success? While image data has been the stalwart for deep learning use cases since the proverbial “ AlexNet moment ” in 2011-2012, and a renaissance in NLP over the past 2-3 years has accelerated emphasis on text use cases, we note that structured data is at the top of the list in enterprise.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Occam's Razor

SEPTEMBER 24, 2012

FBe's recommendation was (paraphrasing a 35 min talk): Don't invent new metrics, use online versions of Reach and GRPs to measure success. Because we don't understand the uniqueness, we fall back on profoundly sub-optimal old world metrics like Reach or Online GRP equivalents. Metrics are a problem.

Advertising 165

Advertising ROI Metrics Marketing 165

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

1]" Statistics, as a discipline, was largely developed in a small data world. With more features come more potential post hoc hypotheses about what is driving metrics of interest, and more opportunity for exploratory analysis. Data was expensive to gather, and therefore decisions to collect data were generally well-considered.

Experimentation 62

Experimentation Testing Statistics Metrics 62

The Unofficial Google Data Science Blog

JULY 18, 2023

Once we’ve answered that, we will then define and use metrics to understand the quality of human-labeled data, along with a measurement framework that we call Cross-replication Reliability or xRR. We will follow the example of Janson and Olsson , and start from this generalized definition of the metric, which they call iota.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

datapine

AUGUST 29, 2022

And with that understanding, you’ll be able to tap into the potential of data analysis to create strategic advantages, exploit your metrics to shape them into stunning business dashboards , and identify new opportunities or at least participate in the process. Microsoft, Alibaba, Taobao, WebMD, Spotify, Yelp” according to Marz himself.

Big Data 263

Big Data Data Analytics Analytics Data mining 263