ABSTRACT
Chapter 12 extends some of the machine learning concepts that we introduced in Chapter 6 and expands them to tackles more difficult models. Machine learning can range from almost any use of a computers (machine) performing calculations and analysis measures to the applications of artificial intelligence (AI) or neural networks in the computer's calculations and analysis methods. The defining characteristic of machine learning is the focus on using algorithmic methods to improve descriptive, predictive, and prescriptive performance in real-world contexts. In this chapter, we will discuss some common techniques such as the gradient method, genetic algorithm, and simulated annealing to handle our problems.
