Student will study/will have previously studied the basis of neural networks including perceptrons, layering, gradient descent, and backpropogation. They will then implement one or more perceptron types (step, linear, sigmoid, tanh) and implement a simple neural network.
This specific project can be tackled from either a machine learning or software engineering approach (using object-oriented design principles).
Grey, B. (2019). Manually Coding a Neural Network. Retrieved from https://digitalcommons.harrisburgu.edu/cisc_pti/11