Questions

1. We went through a lot in this chapter. You can use the framework provided to investigate the properties of neural networks. Try several activation functions, or different settings for convolutions to see what changes in the training process.
2. Draw a diagram of an artificial neuron and label the parts. Look up a natural, human biological neuron, and compare.
3. What features of a real neuron and an artificial neuron are the same?
4. What are different?
5. What relationship does the first layer of a neural network have to the input?
6. What relationship does the last layer of a neural network have to the output?
7. Look up three kinds of loss functions and describe how they work. Include mean square loss and the two kinds of cross entropy loss.
8. What would you change if your network trained to 40% and got "stuck", or was unable to learn anything further?

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