Learning Objectives

Demonstrate proficiency in the following areas:

LO 2.2.2 Perceptron neurons

For example:

A. Calculate the output of a perceptron neuron.

B. Describe the intuition of a perceptron as a decision-making device.

C. Describe a perceptron as a NAND gate and what it implies for perceptron networks

concerning computing logical functions.

D. Explain how perceptron neurons are more than new types of NAND gates.

Reading 2.2: Nielsen, M. A. (2015). Using Neural Networks to Recognize Handwritten Digits. In Neural Networks and Deep Learning, Determination Press.

Article URL: http://neuralnetworksanddeeplearning.com/chap1.html