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20 Machine Learning/Artificial Intelligence Influencers To Follow In 2020

Hacker Earth Developers Blog

Machine Learning (ML) is emerging as one of the hottest fields today. The Machine Learning market is ever-growing, predicted to scale up at a CAGR of 43.8% The Machine Learning market is ever-growing, predicted to scale up at a CAGR of 43.8% billion by the end of 2025. billion by the end of 2025.

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20 Machine Learning/Artificial Intelligence Influencers To Follow In 2020

Hacker Earth Developers Blog

Machine Learning (ML) is emerging as one of the hottest fields today. The Machine Learning market is ever-growing, predicted to scale up at a CAGR of 43.8% The Machine Learning market is ever-growing, predicted to scale up at a CAGR of 43.8% billion by the end of 2025. billion by the end of 2025.

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Agentic AI design: An architectural case study

CIO

From obscurity to ubiquity, the rise of large language models (LLMs) is a testament to rapid technological advancement. Just a few short years ago, models like GPT-1 (2018) and GPT-2 (2019) barely registered a blip on anyone’s tech radar. In 2024, a new trend called agentic AI emerged. Do you see any issues?

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How companies around the world apply machine learning

O'Reilly Media - Data

The growing role of data and machine learning cuts across domains and industries. Companies continue to use data to improve decision-making (business intelligence and analytics) and for automation (machine learning and AI). We have a tutorial and sessions to help companies learn how to comply with GDPR.

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A Guide to Designing Delightful Dashboards

Speaker: Daniel O'Sullivan, Product Designer, nCino and Jeff Hudock, Senior Product Manager, nCino

We’ve all seen the increasing industry trend of artificial intelligence and big data analytics. May 23, 2018 09:30 AM PST, 12:30 PM EST, 5:30 PM GMT In a world of information overload, it's more important than ever to have a dashboard that provides data that's not only interesting but actually relevant and timely.

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Application of advanced analytics and machine learning in the banking industry

Hacker Earth Developers Blog

Banks have always been custodian of customer data, but they lack the technological and analytical capability to derive value from the data. On the other hand, fintech companies have the analytical capabilities and, thanks to payments services directives, they now have access to valuable data. Impact areas. Source: McKinsey.

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Unlocking AI: Machine learning as a service

CIO

On top of this, the rate at which this data is being created is expected to increase at such an extent that IDC predicts the global datasphere will grow from 33 zettabytes (ZB) in 2018 to 175 ZB by 2025 [2]. billion in 2022, more than three times that in 2018 [3], while the total global business value derived from AI is forecast to reach $3.9