What’s The Role Of Weights And Bias In a Neural Network?
Understand Neural networks’ s weights and bias in a most comprehensive way.
Published in
9 min readJul 24, 2020
Introduction
We all know that an Artificial Neuron is a basic building block of a neural network. Before we get into the topic, “what is the role of weights and bias in a Neural Network “, let us understand the skeleton of this Artificial Neuron.
Components of the basic Artificial Neuron:
- Inputs: Inputs are the set of values for which we need to predict a output value. They can be viewed as features or attributes in a dataset.
- Weights: weights are the real values that are attached with each input/feature and they convey the importance of that corresponding feature in predicting the final output. (will discuss about this in-detail in this article)
- Bias: Bias is used for shifting the activation function towards left or right, you can compare this to y-intercept in the line equation. (will discuss more about this in this article)
- Summation Function: The work of the…
