The goal of this exercise is to learn step by step the different elements of a simple two layer network by implementing it from scratch. This exercise was completed as a lab assignment in Florida Poly's Machine Learning course in Spring 2020.
Steps:
- setup the network, namely define the number of layers and units per layer
- initialize the parameters (w's and b's)
- Use tanh as the activation function of the hidden layer, and sigmoid for the output layer
- Compute the cross entropy loss
- Implement forward and backward propagation
The author of the original Jupyter Notebook is Andrew Ng. This Notebook was modified by Dr. Luis Jaimes at Florida Poly for use as a lab assignment.