Perceptron
Learn about the most basic type of neural net, the single neuron perceptron! You will use it to divide linearly-separable data.
StartKey Concepts
Review core concepts you need to learn to master this subject
Perceptron Bias Term
Perceptrons as Linear Classifiers
Perceptron Weighted Sum
Optimizing Perceptron Weights
Adjusting 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
Portfolio projects that showcase your new skills
How you'll master it
Stress-test your knowledge with quizzes that help commit syntax to memory