The Perceptron is an algorithm used for supervised learning of binary classifiers.
Binary classifiers decide whether an input, usually represented by a series of vectors, belongs to a specific class.
In short, a perceptron has 1 filter that has one character property.
When people say Neuron/Unit/Node when they mean the structure of a Perceptron.
python3 sample_numpy.py
python3 sample_scratch.py
python3 sample_sklearn.py
- https://deepai.org/machine-learning-glossary-and-terms/perceptron
- https://towardsdatascience.com/what-the-hell-is-perceptron-626217814f53
- https://computing.dcu.ie/~humphrys/Notes/Neural/single.neural.html
- https://www.youtube.com/watch?v=aiDv1NPdXvU
- https://machinelearningmastery.com/tutorial-first-neural-network-python-keras/
- https://www.machinecurve.com/index.php/2019/07/24/why-you-cant-truly-create-rosenblatts-perceptron-with-keras/
- https://machinelearningmastery.com/implement-perceptron-algorithm-scratch-python/