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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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Anomaly detection in machine learning: Finding outliers for optimization of business functions

IBM Big Data Hub

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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Interview With a Crypto Scam Investment Spammer

Krebs on Security

“I make Telegram bots and other rubbish cheaply,” reads one February 2020 sales thread from Zipper. His resume also says he is a data science intern at Mondi Group , an Austrian manufacturer of sustainable packaging and paper. Mr. Proshutinskiy did not respond to requests for comment.

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How we used generative AI to run a generative AI hackathon

Collibra

As the data intelligence company, we’ve long anticipated broad adoption of AI, and Collibrians with data science and machine learning expertise have been working diligently on ways to apply AI/ML. She said some of the first results were more relevant for a manufacturing hackathon than a software hackathon.

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Generative AI use cases for the enterprise

IBM Big Data Hub

Key considerations: Tech stack: Ensure your existing technology infrastructure can handle the demands of AI models and data processing. Teamwork: Assemble a team with expertise in AI, data science and your industry. Data: High-quality, relevant data is the fuel that powers generative AI success.

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GUEST ESSAY: The story behind how DataTribe is helping to seed ‘Cybersecurity Valley’ in Maryland

The Last Watchdog

It’s a cybersecurity and data science “foundry” that uniquely helps create, finance and intensely coach brand-new startups manned by former cybersecurity and data science veterans of select federal research centers and national laboratories. Also disrupting new technology categories are BlueRidge AI and Refirm Labs.

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10 everyday machine learning use cases

IBM Big Data Hub

Machine learning in marketing and sales According to Forbes , marketing and sales teams prioritize AI and ML more than any other enterprise department. Marketers use ML for lead generation, data analytics, online searches and search engine optimization (SEO).