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:
Read more... 
Source: Packt Hub 
 
 

 
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