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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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Enterprise Data Science Workflows with AMPs and Streamlit

Cloudera

Here in the virtual Fast Forward Lab at Cloudera , we do a lot of experimentation to support our applied machine learning research, and Cloudera Machine Learning product development. Only through hands-on experimentation can we discern truly useful new algorithmic capabilities from hype. Not all of them require a unique front-end.

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Pair Programming with AI

O'Reilly on Data

Shortly after IBM’s Watson beat the world Jeopardy champions, IBM invited me to see a presentation about it. That cyclic process, which is about collaboration between software developers and customers, may be exactly what we need to get beyond the “AI as Oracle” interaction.

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The top 15 big data and data analytics certifications

CIO Business Intelligence

Organization: CompTIA Price: US$246 How to prepare: CompTIA offers elearning, interactive labs, and exam prep through CertMaster, study guides, and instructor-led training. They can visualize and present data findings in dashboards, presentations, and commonly used visualization platforms.

Big Data 126
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Digital listening reveals 3 leading innovation drivers

CIO Business Intelligence

It surpasses blockchain and metaverse projects, which are viewed as experimental or in the pilot stage, especially by established enterprises. Big Data collection at scale is increasing across industries, presenting opportunities for companies to develop AI models and leverage insights from that data.

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Interview with: Sankar Narayanan, Chief Practice Officer at Fractal Analytics

Corinium

present a significant barrier to adoption of the latest and greatest approaches. It is also important to have a strong test and learn culture to encourage rapid experimentation. Newer methods can work with large amounts of data and are able to unearth latent interactions. In addition, the traditional challenges remain.

Insurance 250
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How to get powerful and actionable insights from any and all of your data, without delay

Cloudera

By enabling their event analysts to monitor and analyze events in real time, as well as directly in their data visualization tool, and also rate and give feedback to the system interactively, they increased their data to insight productivity by a factor of 10. . This led them to fall behind. Our solution: Cloudera Data Visualization.