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

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