DSPA Chapter 10 SVM ClassificationIn this chapter, we are going to cover two very powerful
machine-learning algorithms. These techniques have complex mathematical
formulations, however, efficient algorithms and reliable software
packages have been developed to utilize them for various practical
applications. We will (1) describe Neural Networks as analogues of
biological neurons, (2) develop hands-on a neural net that can be
trained to compute the square-root function, (3) describe support vector
machine (SVM) classification, and (4) complete several case-studies,
including optical character recognition (OCR), the Iris flowers, Google
Trends and the Stock Market, and Quality of Life in chronic disease.
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