If you are a deep learning practitioner or someone who wants to get into the world of deep learning,
you might be well acquainted with neural networks already, as Packt Hub reports.
Neural
networks, inspired by biological neural networks, are pretty useful when
it comes to solving complex, multi-layered computational problems. Deep
learning has stood out pretty well in several high-profile research
fields – including facial and speech recognition, natural language
processing, machine translation, and more.
In this article, we look at the top 5 popular and widely-used deep
learning architectures you should know in order to advance your
knowledge or deep learning research.
Convolutional Neural Networks
Convolutional Neural Networks, or CNNs in short, are the popular
choice of neural networks for different Computer Vision tasks such as
image recognition. The name ‘convolution’ is derived from a mathematical
operation involving the convolution of different functions.
There are 4 primary steps or stages in designing a CNN:
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Source: Packt Hub