Programming Tech

The presentation begins with a page from MathWorks e-book “Introducing Machine Learning,” which summarizes various kinds of machine learning algorithms, including supervised learning, of which classification and regression are examples, and unsupervised learning, of which clustering is an example. Several different neural networks and statistical algorithms are listed as part of these three categories of techniques. The first half of the talk gives a brief overview into development of neural network models. The model of a biological neural cell was developed in 1943, followed by modeling biological neural networks, resulting in a multilayer perceptron network, also called a feedforward network. These networks are listed as supervised algorithms having an input, an output, and several hidden layers. Structure and parameters are chosen in advance, except for the weights. The weights are determined based on input-output data using numerical optimization methods to minimize the mean squar