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Bringing an AI Product to Market

O'Reilly on Data

The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you’ve succeeded. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. Agreeing on metrics.

Marketing 362
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Try semantic search with the Amazon OpenSearch Service vector engine

AWS Big Data

Lexical search looks for words in the documents that appear in the queries. Background A search engine is a special kind of database, allowing you to store documents and data and then run queries to retrieve the most relevant ones. OpenSearch Service supports a variety of search and relevance ranking techniques.

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The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

To win in business you need to follow this process: Metrics > Hypothesis > Experiment > Act. We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. That metric is tied to a KPI.

Metrics 156
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Digital transformation’s fundamental change management mistake

CIO Business Intelligence

Joanne Friedman, PhD, CEO, and principal of smart manufacturing at Connektedminds, says orchestrating success in digital transformation requires a symphony of integration across disciplines : “CIOs face the challenge of harmonizing diverse disciplines like design thinking, product management, agile methodologies, and data science experimentation.

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7 steps for turning shadow IT into a competitive edge

CIO Business Intelligence

Equally important is communicating with stakeholders how to onboard technology requests, sharing how departmental technology needs are prioritized, documenting stakeholder responsibilities when seeking new technologies, and providing the status of active programs.

IT 131
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Amazon OpenSearch Service search enhancements: 2023 roundup

AWS Big Data

Lexical search In lexical search, the search engine compares the words in the search query to the words in the documents, matching word for word. It similarly codes the query as a vector and then uses a distance metric to find nearby vectors in the multi-dimensional space to find matches.

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Building AI with AutoML and Composable ML

DataRobot

After adding the preferred code, teams can take advantage of the existing DataRobot capabilities, such as metrics, explainability, visualizations, deployment, monitoring, collaboration, and governance. In data science , the best results come through experimentation. So let’s dig in!