This document provides exercises for a tutorial on multilayer neural networks and deep learning. It includes 9 exercises covering topics like:
- Deriving and writing the weight update rule for the hyperbolic tangent sigmoid activation function 
- Calculating the number of weights in a sample neural network
- Factors that influence the performance of the backpropagation algorithm, like network architecture
- The effect of learning rate on convergence in backpropagation
- The advantage of using momentum in backpropagation
- How too many hidden neurons can lead to poor generalization
- An example of convolution in deep neural networks
- Working through a detailed backpropagation example to understand the forward and backward passes

COMP3308/3608 Artificial Intelligence Week 9 Tutorial Exercises Multilayer Neural Networks 2. Deep Learning PDF

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