# Perceptron

Learn about the most basic type of neural net, the single neuron perceptron! You will use it to divide linearly-separable data.

Start## Key Concepts

Review core concepts you need to learn to master this subject

Perceptron Bias Term

Perceptrons as Linear Classifiers

Adjusting Perceptron Weights

Perceptron Weighted Sum

Optimizing Perceptron Weights

Introduction to Perceptrons

Perceptron Activation Functions

Perceptron Training Error

Perceptron Bias Term

Perceptron Bias Term

`weighted_sum = x1*w1 + x2*w2 + x3*w3 + 1*wbias`

The *bias* term is an adjustable, numerical term added to a perceptron’s *weighted sum* of inputs and weights that can increase classification model accuracy.

The addition of the bias term is helpful because it serves as another model parameter (in addition to weights) that can be tuned to make the model’s performance on training data as good as possible.

The default input value for the *bias* weight is `1`

and the weight value is adjustable.

## What you'll create

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## How you'll master it

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