Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test ...

Deep learning network compression techniques have emerged as a crucial research area, aiming to reduce the computational and storage requirements of neural networks without significantly compromising ...

Understand Local Response Normalization (LRN) in deep learning: what it is, why it was introduced, and how it works in ...

Article reviewed by Grace Lindsay, PhD from New York University. Scientists design ANNs to function like neurons. 6 They write lines of code in an algorithm such that there are nodes that each contain ...

The recently published book Understanding Deep Learning by [Simon J. D. Prince] is notable not only for focusing primarily on the concepts behind Deep Learning — which should make it highly accessible ...

Artificial intelligence is everywhere these days, but the fundamentals of how this influential new technology work can be difficult to wrap your head around. Two of the most important fields in AI ...

Artificial intelligence (AI) is increasingly prevalent, integrated into phone apps, search engines and social media platforms as well as supporting myriad research applications. Of particular interest ...