7 Types of Activation Functions in Neural Network

Activation functions are the most crucial part of any neural network in deep learning. In deep learning, very complicated tasks are image classification, language transformation, object detection, etc which are needed to address with the help of neural networks and activation function. So, without it, these tasks are extremely complex to handle.

In the nutshell, a neural network is a very potent technique in machine learning that basically imitates how a brain understands, how? The brain receives the stimuli, as input, from the environment, processes it and then produces the output accordingly.

Introduction

The neural network activation functions, in general, are the most significant component of Deep Learning, they are fundamentally used for determining the output of deep learning models, its accuracy, and performance efficiency of the training model that can design or divide a huge scale neural network.

Activation functions have left considerable effects on the ability of neural networks to converge and convergence speed, don’t you want to how? Let’s continue with an introduction to the activation function, types of activation functions & their importance and limitations through this blog.

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