IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

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IBM Big Data Hub

DECEMBER 20, 2023

Artificial intelligence (AI) is a transformative force. The automation of tasks that traditionally relied on human intelligence has far-reaching implications, creating new opportunities for innovation and enabling businesses to reinvent their operations. What is an AI strategy?

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IBM Big Data Hub

DECEMBER 19, 2023

Anomalies are not inherently bad, but being aware of them, and having data to put them in context, is integral to understanding and protecting your business. The challenge for IT departments working in data science is making sense of expanding and ever-changing data points.

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IBM Big Data Hub

FEBRUARY 13, 2024

Generative AI ( artificial intelligence ) promises a similar leap in productivity and the emergence of new modes of working and creating. Key considerations: Tech stack: Ensure your existing technology infrastructure can handle the demands of AI models and data processing.

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IBM Big Data Hub

OCTOBER 16, 2023

Machine learning (ML)—the artificial intelligence (AI) subfield in which machines learn from datasets and past experiences by recognizing patterns and generating predictions—is a $21 billion global industry projected to become a $209 billion industry by 2029.

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ARMA International

SEPTEMBER 13, 2021

The nomenclature can extend to include Data as a Service (DaaS), Content as a Service (CaaS), and Managed Content as a Service (MCaaS) to deliver digital interaction experiences to customers. More recent technology trends include Blockchain as a Service (BaaS) and Artificial Intelligence as a Service (AIaaS).

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Digital transformation Blockchain IT Computer and Electronics 59

IBM Big Data Hub

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

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