Deep Learning: When Should You Use It?

Deep learning, which is a subset of AI (Artificial Intelligence), has been around since the 1950s. It’s focused on developing systems that mimic the brain’s neural network structure.

Yet it was not until the 1980s that deep learning started to show promise, spurred by the pioneering theories of researchers like Geoffrey Hinton, Yoshua Bengio and Yann Lecun. There was also the benefit of accelerating improvements in computer power.

Despite all this, there remained lots of skepticism. Deep learning approaches still looked more like interesting academic exercises that were not ready for prime time.

But this all changed in a big way in 2012, when Hinton, Ilya Sutskever, and Alex Krizhevsky used sophisticated deep learning to recognize images in an enormous dataset. The results were stunning, as they blew away previous records. So began the deep learning revolution. READ MORE ON: FORBES

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BasicsYusra Hamid