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. Based on results of value identified for Facebook, optimize their advertising mix strategy for future product launches. I don't think it is simply a metrics/measurement problem.

Advertising 165

Advertising ROI Metrics Marketing 165

DataRobot Blog

MAY 26, 2022

In this post, we will dive deeper into how members from both the first and second line of defense within a financial institution can adapt their model validation strategies in the context of modern ML methods. 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

Occam's Razor

MAY 14, 2012

Bonus One: Read: Brand Measurement: Analytics & Metrics for Branding Campaigns ]. There are many different tools, both online and offline, that measure the elusive metric called brand strength. Amazon is an interesting example. Brand strength is built over time using online and offline advertising.

Measurement 128

Measurement Analytics Advertising Marketing 128

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

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

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 61

Experimentation Testing Statistics Metrics 61