Remove Deep Learning Remove Experimentation Remove Metadata Remove Optimization
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Bringing an AI Product to Market

O'Reilly on Data

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
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What you need to know about product management for AI

O'Reilly on Data

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.

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Of Muffins and Machine Learning Models

Cloudera

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. Further auditing can be enabled at a session level so administrators can request key metadata about each CML process. Figure 03: lineage.yaml.

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Themes and Conferences per Pacoid, Episode 11

Domino Data Lab

In other words, using metadata about data science work to generate code. SQL optimization provides helpful analogies, given how SQL queries get translated into query graphs internally , then the real smarts of a SQL engine work over that graph. On deck this time ’round the Moon: program synthesis. Software writes Software?

Metadata 105