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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

” “Data science” was first used as an independent discipline in 2001. Both data science and machine learning are used by data engineers and in almost every industry. Some examples of data science use cases include: An international bank uses ML-powered credit risk models to deliver faster loans over a mobile app.

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

Also, while surveying the literature two key drivers stood out: Risk management is the thin-edge-of-the-wedge ?for We find ways to improve machine learning so that it requires orders of magnitude more data, e.g., deep learning with neural networks. A very big mess since circa 2001, and now becoming quite a dangerous mess.

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Data Science, Past & Future

Domino Data Lab

and drop your deep learning model resource footprint by 5-6 orders of magnitude and run it on devices that don’t even have batteries. What I’m trying to say is this evolution of system architecture, the hardware driving the software layers, and also, the whole landscape with regard to threats and risks, it changes things.

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Data Science at The New York Times

Domino Data Lab

In 2001, Bill Cleveland writes this article saying, “You are doing it wrong.” You can sleep at night as a data scientician and you know you’re not building a random number generator, but the people from product, they don’t want to know just that you can predict who’s going to be at risk.