O'Reilly on Data

JULY 28, 2020

Without clarity in metrics, it’s impossible to do meaningful experimentation. AI PMs must ensure that experimentation occurs during three phases of the product lifecycle: Phase 1: Concept During the concept phase, it’s important to determine if it’s even possible for an AI product “ intervention ” to move an upstream business metric.

Marketing 362

Marketing Experimentation Metrics Testing 362

O'Reilly on Data

MARCH 31, 2020

You might have millions of short videos , with user ratings and limited metadata about the creators or content. Job postings have a much shorter relevant lifetime than movies, so content-based features and metadata about the company, skills, and education requirements will be more important in this case.

Management 332

Management Machine Learning Experimentation Metrics 332

Cloudera

FEBRUARY 16, 2022

blueberry spacing) is a measure of the model’s interpretability. SDX provides open metadata management and governance across each deployed environment by allowing organisations to catalogue, classify as well as control access to and manage all data assets. Machine Learning Model Visibility . Model Visibility.

Machine Learning 81

Machine Learning Modeling Metadata Recreation/Entertainment 81