Activation Functions in Deep Learning | Sigmoid, Tanh and Relu Activation Function

In artificial neural networks, each neuron forms a weighted sum of its inputs and passes the resulting scalar value through a function referred to as an activation function or transfer function. In this video, we explain the basics of Sigmoid, Tanh, and Relu—important parts of how computers learn.

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⌚Time Stamps⌚

00:00 - Intro
00:47 - What are activation functions?
03:28 - Importance of AF
04:58 - Code Demo
06:38 - Why activation functions are needed?
11:05 - Ideal Activation function
18:41 - Sigmoid Activation Function
20:37 - Advantages
22:56 - Disadvantages
36:15 - Tan h Activation Function
38:00 - Advantages
39:02 - Disadvantages
40:17 - Relu Activation Function
40:50 - Advantages
42:43 - Disadvantages
44:24 - Outro