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In a neural network, there is the concept of loss, which is used to calculate performance. The higher the loss, the poorer the performance of the neural network, that is why we always try to minimize the loss so that the neural network performs better.


Inspired by human brains, Artificial Neural Networks (ANN) are now being utilised by enterprises across the globe to solve a number of complex computing tasks like speech recognition, computer vision, stock market prediction, among others. In this article, we list down 6 techniques which can be used to optimise deep neural networks. 1| Stochastic Gradient…
The post 6 Techniques From Leading AI Scientists To Optimise Deep Neural Networks appeared first on Analytics India Magazine.

