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The Future of Machine Learning in Cybersecurity

CIO

Machine learning (ML) is a commonly used term across nearly every sector of IT today. And while ML has frequently been used to make sense of big data—to improve business performance and processes and help make predictions—it has also proven priceless in other applications, including cybersecurity.

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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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2 Innovations That Can Tip the Balance in Cybersecurity

CIO

Army Major General and Vice President and Federal Chief Security Officer for Palo Alto Networks What critical innovations can change the balance in cybersecurity, providing those of us responsible for defending our organizations with more capabilities against those who would do us harm? They are: Innovations in automation.

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Embedding BI: Architectural Considerations and Technical Requirements

While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Holding onto old BI technology while everything else moves forward is holding back organizations.

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Innovative data integration in 2024: Pioneering the future of data integration

CIO

In the age of big data, where information is generated at an unprecedented rate, the ability to integrate and manage diverse data sources has become a critical business imperative. Traditional data integration methods are often cumbersome, time-consuming, and unable to keep up with the rapidly evolving data landscape.

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Making AI accessible leads to greater innovation

CIO

AI is expensive, as workloads are generally hosted in the cloud, but the sheer amount of data involved in building an effective AI routine result in big data costs. With so much innovation available through AI, organisations are facing a disrupt or be disrupted scenario.