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The Convolutional Neural Network - Theory and Implementation of LeNet-5 and AlexNet
Learning objectives Understand the principles behind the creation of the convolutional network Gain an intuitive understanding of the convolution (feature map) and pooling (subsampling) operations Develop a basic code implementation of the LeNet-5 and AlexNet networks in Python Identify the similarities and differences between human vision and convolutional networks Historical...
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The Multilayer Perceptron - Theory and Implementation of the Backpropagation Algorithm
Learning objectives Understand the principles behind the creation of the multilayer perceptron Identify how the multilayer perceptron overcame many of the limitations of previous models Expand understanding of learning via gradient descent methods Develop a basic code implementation of the multilayer perceptron in Python Be aware of the main limitations...
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The ADALINE - Theory and Implementation of the First Neural Network Trained With Gradient Descent
Learning objectives Understand the principles behind the creation of the ADALINE Identify the similarities and differences between the perceptron and the ADALINE Acquire an intuitive understanding of learning via gradient descent Develop a basic code implementation of the ADALINE in Python Determine what kind of problems can and can’t be...