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\contentsline {figure}{\numberline {2.1}{\ignorespaces Illustration of a neural network}}{2}% 
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\contentsline {figure}{\numberline {2.2}{\ignorespaces Plots of the activation functions\relax }}{4}% 
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\contentsline {figure}{\numberline {2.3}{\ignorespaces Structure of a single neuron\relax }}{4}% 
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\contentsline {figure}{\numberline {3.1}{\ignorespaces Overfitting of shallow neural networks}}{10}% 
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\contentsline {figure}{\numberline {3.2}{\ignorespaces Comparison of shallow neural networks and regression splines}}{21}% 
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\contentsline {figure}{\numberline {4.1}{\ignorespaces Signal smoothing using convolution}}{23}% 
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\contentsline {figure}{\numberline {4.2}{\ignorespaces Channel separation of color image}}{24}% 
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\contentsline {figure}{\numberline {4.3}{\ignorespaces Convolution applied on image}}{25}% 
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\contentsline {figure}{\numberline {4.4}{\ignorespaces MNIST data set}}{29}% 
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\contentsline {figure}{\numberline {4.5}{\ignorespaces architecture\relax }}{29}% 
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\contentsline {figure}{\numberline {4.6}{\ignorespaces Performance comparison of SDG and GD}}{30}% 
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\contentsline {figure}{\numberline {4.7}{\ignorespaces Performance comparison of training algorithms}}{35}% 
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\contentsline {figure}{\numberline {4.8}{\ignorespaces Image data generation}}{37}% 
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\contentsline {figure}{\numberline {4.9}{\ignorespaces Performance comparison of overfitting measures}}{38}% 
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\contentsline {figure}{\numberline {4.10}{\ignorespaces Fashion MNIST data set}}{39}% 
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\contentsline {figure}{\numberline {4.11}{\ignorespaces \relax }}{41}% 
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\contentsline {figure}{\numberline {4.12}{\ignorespaces Sample pictures of the mnist fashioyn dataset, one per class.\relax }}{41}%